2168 lines
69 KiB
C
2168 lines
69 KiB
C
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/*
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* psymodel.c
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*
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* Copyright (c) 1999-2000 Mark Taylor
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* Copyright (c) 2001-2002 Naoki Shibata
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* Copyright (c) 2000-2003 Takehiro Tominaga
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* Copyright (c) 2000-2012 Robert Hegemann
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* Copyright (c) 2000-2005 Gabriel Bouvigne
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* Copyright (c) 2000-2005 Alexander Leidinger
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*
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* This library is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Library General Public
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* License as published by the Free Software Foundation; either
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* version 2 of the License, or (at your option) any later version.
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*
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* This library is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Library General Public License for more details.
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*
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* You should have received a copy of the GNU Library General Public
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* License along with this library; if not, write to the
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* Free Software Foundation, Inc., 59 Temple Place - Suite 330,
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* Boston, MA 02111-1307, USA.
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*/
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/* $Id: psymodel.c,v 1.216 2017/09/06 19:38:23 aleidinger Exp $ */
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/*
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PSYCHO ACOUSTICS
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This routine computes the psycho acoustics, delayed by one granule.
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Input: buffer of PCM data (1024 samples).
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This window should be centered over the 576 sample granule window.
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The routine will compute the psycho acoustics for
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this granule, but return the psycho acoustics computed
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for the *previous* granule. This is because the block
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type of the previous granule can only be determined
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after we have computed the psycho acoustics for the following
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granule.
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Output: maskings and energies for each scalefactor band.
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block type, PE, and some correlation measures.
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The PE is used by CBR modes to determine if extra bits
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from the bit reservoir should be used. The correlation
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measures are used to determine mid/side or regular stereo.
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*/
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/*
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Notation:
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barks: a non-linear frequency scale. Mapping from frequency to
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barks is given by freq2bark()
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scalefactor bands: The spectrum (frequencies) are broken into
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SBMAX "scalefactor bands". Thes bands
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are determined by the MPEG ISO spec. In
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the noise shaping/quantization code, we allocate
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bits among the partition bands to achieve the
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best possible quality
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partition bands: The spectrum is also broken into about
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64 "partition bands". Each partition
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band is about .34 barks wide. There are about 2-5
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partition bands for each scalefactor band.
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LAME computes all psycho acoustic information for each partition
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band. Then at the end of the computations, this information
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is mapped to scalefactor bands. The energy in each scalefactor
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band is taken as the sum of the energy in all partition bands
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which overlap the scalefactor band. The maskings can be computed
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in the same way (and thus represent the average masking in that band)
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or by taking the minmum value multiplied by the number of
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partition bands used (which represents a minimum masking in that band).
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*/
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/*
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The general outline is as follows:
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1. compute the energy in each partition band
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2. compute the tonality in each partition band
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3. compute the strength of each partion band "masker"
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4. compute the masking (via the spreading function applied to each masker)
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5. Modifications for mid/side masking.
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Each partition band is considiered a "masker". The strength
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of the i'th masker in band j is given by:
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s3(bark(i)-bark(j))*strength(i)
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The strength of the masker is a function of the energy and tonality.
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The more tonal, the less masking. LAME uses a simple linear formula
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(controlled by NMT and TMN) which says the strength is given by the
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energy divided by a linear function of the tonality.
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*/
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/*
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s3() is the "spreading function". It is given by a formula
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determined via listening tests.
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The total masking in the j'th partition band is the sum over
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all maskings i. It is thus given by the convolution of
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the strength with s3(), the "spreading function."
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masking(j) = sum_over_i s3(i-j)*strength(i) = s3 o strength
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where "o" = convolution operator. s3 is given by a formula determined
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via listening tests. It is normalized so that s3 o 1 = 1.
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Note: instead of a simple convolution, LAME also has the
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option of using "additive masking"
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The most critical part is step 2, computing the tonality of each
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partition band. LAME has two tonality estimators. The first
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is based on the ISO spec, and measures how predictiable the
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signal is over time. The more predictable, the more tonal.
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The second measure is based on looking at the spectrum of
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a single granule. The more peaky the spectrum, the more
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tonal. By most indications, the latter approach is better.
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Finally, in step 5, the maskings for the mid and side
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channel are possibly increased. Under certain circumstances,
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noise in the mid & side channels is assumed to also
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be masked by strong maskers in the L or R channels.
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Other data computed by the psy-model:
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ms_ratio side-channel / mid-channel masking ratio (for previous granule)
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ms_ratio_next side-channel / mid-channel masking ratio for this granule
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percep_entropy[2] L and R values (prev granule) of PE - A measure of how
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much pre-echo is in the previous granule
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percep_entropy_MS[2] mid and side channel values (prev granule) of percep_entropy
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energy[4] L,R,M,S energy in each channel, prev granule
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blocktype_d[2] block type to use for previous granule
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*/
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#ifdef HAVE_CONFIG_H
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# include <config.h>
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#endif
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#include <float.h>
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#include "lame.h"
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#include "machine.h"
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#include "encoder.h"
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#include "util.h"
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#include "psymodel.h"
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#include "lame_global_flags.h"
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#include "fft.h"
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#include "lame-analysis.h"
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#define NSFIRLEN 21
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#ifdef M_LN10
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#define LN_TO_LOG10 (M_LN10/10)
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#else
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#define LN_TO_LOG10 0.2302585093
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#endif
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/*
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L3psycho_anal. Compute psycho acoustics.
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Data returned to the calling program must be delayed by one
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granule.
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This is done in two places.
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If we do not need to know the blocktype, the copying
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can be done here at the top of the program: we copy the data for
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the last granule (computed during the last call) before it is
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overwritten with the new data. It looks like this:
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0. static psymodel_data
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1. calling_program_data = psymodel_data
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2. compute psymodel_data
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For data which needs to know the blocktype, the copying must be
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done at the end of this loop, and the old values must be saved:
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0. static psymodel_data_old
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1. compute psymodel_data
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2. compute possible block type of this granule
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3. compute final block type of previous granule based on #2.
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4. calling_program_data = psymodel_data_old
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5. psymodel_data_old = psymodel_data
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*/
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/* psycho_loudness_approx
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jd - 2001 mar 12
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in: energy - BLKSIZE/2 elements of frequency magnitudes ^ 2
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gfp - uses out_samplerate, ATHtype (also needed for ATHformula)
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returns: loudness^2 approximation, a positive value roughly tuned for a value
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of 1.0 for signals near clipping.
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notes: When calibrated, feeding this function binary white noise at sample
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values +32767 or -32768 should return values that approach 3.
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ATHformula is used to approximate an equal loudness curve.
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future: Data indicates that the shape of the equal loudness curve varies
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with intensity. This function might be improved by using an equal
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loudness curve shaped for typical playback levels (instead of the
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ATH, that is shaped for the threshold). A flexible realization might
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simply bend the existing ATH curve to achieve the desired shape.
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However, the potential gain may not be enough to justify an effort.
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*/
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static FLOAT
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psycho_loudness_approx(FLOAT const *energy, FLOAT const *eql_w)
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{
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int i;
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FLOAT loudness_power;
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loudness_power = 0.0;
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/* apply weights to power in freq. bands */
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for (i = 0; i < BLKSIZE / 2; ++i)
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loudness_power += energy[i] * eql_w[i];
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loudness_power *= VO_SCALE;
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return loudness_power;
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}
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/* mask_add optimization */
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/* init the limit values used to avoid computing log in mask_add when it is not necessary */
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/* For example, with i = 10*log10(m2/m1)/10*16 (= log10(m2/m1)*16)
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*
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* abs(i)>8 is equivalent (as i is an integer) to
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* abs(i)>=9
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* i>=9 || i<=-9
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* equivalent to (as i is the biggest integer smaller than log10(m2/m1)*16
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* or the smallest integer bigger than log10(m2/m1)*16 depending on the sign of log10(m2/m1)*16)
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* log10(m2/m1)>=9/16 || log10(m2/m1)<=-9/16
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* exp10 is strictly increasing thus this is equivalent to
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* m2/m1 >= 10^(9/16) || m2/m1<=10^(-9/16) which are comparisons to constants
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*/
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#define I1LIMIT 8 /* as in if(i>8) */
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#define I2LIMIT 23 /* as in if(i>24) -> changed 23 */
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#define MLIMIT 15 /* as in if(m<15) */
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/* pow(10, (I1LIMIT + 1) / 16.0); */
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static const FLOAT ma_max_i1 = 3.6517412725483771;
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/* pow(10, (I2LIMIT + 1) / 16.0); */
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static const FLOAT ma_max_i2 = 31.622776601683793;
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/* pow(10, (MLIMIT) / 10.0); */
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static const FLOAT ma_max_m = 31.622776601683793;
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/*This is the masking table:
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According to tonality, values are going from 0dB (TMN)
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to 9.3dB (NMT).
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After additive masking computation, 8dB are added, so
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final values are going from 8dB to 17.3dB
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*/
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static const FLOAT tab[] = {
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1.0 /*pow(10, -0) */ ,
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0.79433 /*pow(10, -0.1) */ ,
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0.63096 /*pow(10, -0.2) */ ,
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0.63096 /*pow(10, -0.2) */ ,
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0.63096 /*pow(10, -0.2) */ ,
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0.63096 /*pow(10, -0.2) */ ,
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0.63096 /*pow(10, -0.2) */ ,
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0.25119 /*pow(10, -0.6) */ ,
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0.11749 /*pow(10, -0.93) */
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};
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static const int tab_mask_add_delta[] = { 2, 2, 2, 1, 1, 1, 0, 0, -1 };
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#define STATIC_ASSERT_EQUAL_DIMENSION(A,B) enum{static_assert_##A=1/((dimension_of(A) == dimension_of(B))?1:0)}
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inline static int
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mask_add_delta(int i)
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{
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STATIC_ASSERT_EQUAL_DIMENSION(tab_mask_add_delta,tab);
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assert(i < (int)dimension_of(tab));
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return tab_mask_add_delta[i];
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}
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static void
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init_mask_add_max_values(void)
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{
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#ifndef NDEBUG
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FLOAT const _ma_max_i1 = pow(10, (I1LIMIT + 1) / 16.0);
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FLOAT const _ma_max_i2 = pow(10, (I2LIMIT + 1) / 16.0);
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FLOAT const _ma_max_m = pow(10, (MLIMIT) / 10.0);
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assert(fabs(ma_max_i1 - _ma_max_i1) <= FLT_EPSILON);
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assert(fabs(ma_max_i2 - _ma_max_i2) <= FLT_EPSILON);
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assert(fabs(ma_max_m - _ma_max_m ) <= FLT_EPSILON);
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#endif
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}
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/* addition of simultaneous masking Naoki Shibata 2000/7 */
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inline static FLOAT
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vbrpsy_mask_add(FLOAT m1, FLOAT m2, int b, int delta)
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{
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static const FLOAT table2[] = {
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1.33352 * 1.33352, 1.35879 * 1.35879, 1.38454 * 1.38454, 1.39497 * 1.39497,
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1.40548 * 1.40548, 1.3537 * 1.3537, 1.30382 * 1.30382, 1.22321 * 1.22321,
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1.14758 * 1.14758,
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1
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};
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FLOAT ratio;
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if (m1 < 0) {
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m1 = 0;
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}
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if (m2 < 0) {
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m2 = 0;
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}
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if (m1 <= 0) {
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return m2;
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}
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if (m2 <= 0) {
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return m1;
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}
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if (m2 > m1) {
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ratio = m2 / m1;
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}
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else {
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ratio = m1 / m2;
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}
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if (abs(b) <= delta) { /* approximately, 1 bark = 3 partitions */
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/* originally 'if(i > 8)' */
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if (ratio >= ma_max_i1) {
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return m1 + m2;
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}
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else {
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int i = (int) (FAST_LOG10_X(ratio, 16.0f));
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return (m1 + m2) * table2[i];
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}
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}
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if (ratio < ma_max_i2) {
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return m1 + m2;
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}
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if (m1 < m2) {
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m1 = m2;
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}
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return m1;
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}
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/* short block threshold calculation (part 2)
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partition band bo_s[sfb] is at the transition from scalefactor
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band sfb to the next one sfb+1; enn and thmm have to be split
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between them
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*/
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static void
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convert_partition2scalefac(PsyConst_CB2SB_t const *const gd, FLOAT const *eb, FLOAT const *thr,
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FLOAT enn_out[], FLOAT thm_out[])
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{
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FLOAT enn, thmm;
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int sb, b, n = gd->n_sb;
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enn = thmm = 0.0f;
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for (sb = b = 0; sb < n; ++b, ++sb) {
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int const bo_sb = gd->bo[sb];
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int const npart = gd->npart;
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int const b_lim = bo_sb < npart ? bo_sb : npart;
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while (b < b_lim) {
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assert(eb[b] >= 0); /* iff failed, it may indicate some index error elsewhere */
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assert(thr[b] >= 0);
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enn += eb[b];
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thmm += thr[b];
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b++;
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}
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if (b >= npart) {
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enn_out[sb] = enn;
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thm_out[sb] = thmm;
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++sb;
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break;
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}
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assert(eb[b] >= 0); /* iff failed, it may indicate some index error elsewhere */
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assert(thr[b] >= 0);
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{
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/* at transition sfb -> sfb+1 */
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FLOAT const w_curr = gd->bo_weight[sb];
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FLOAT const w_next = 1.0f - w_curr;
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enn += w_curr * eb[b];
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thmm += w_curr * thr[b];
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enn_out[sb] = enn;
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thm_out[sb] = thmm;
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enn = w_next * eb[b];
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thmm = w_next * thr[b];
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}
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}
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/* zero initialize the rest */
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for (; sb < n; ++sb) {
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enn_out[sb] = 0;
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thm_out[sb] = 0;
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}
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}
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static void
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convert_partition2scalefac_s(lame_internal_flags * gfc, FLOAT const *eb, FLOAT const *thr, int chn,
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int sblock)
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{
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PsyStateVar_t *const psv = &gfc->sv_psy;
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PsyConst_CB2SB_t const *const gds = &gfc->cd_psy->s;
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FLOAT enn[SBMAX_s], thm[SBMAX_s];
|
||
|
int sb;
|
||
|
convert_partition2scalefac(gds, eb, thr, enn, thm);
|
||
|
for (sb = 0; sb < SBMAX_s; ++sb) {
|
||
|
psv->en[chn].s[sb][sblock] = enn[sb];
|
||
|
psv->thm[chn].s[sb][sblock] = thm[sb];
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/* longblock threshold calculation (part 2) */
|
||
|
static void
|
||
|
convert_partition2scalefac_l(lame_internal_flags * gfc, FLOAT const *eb, FLOAT const *thr, int chn)
|
||
|
{
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_CB2SB_t const *const gdl = &gfc->cd_psy->l;
|
||
|
FLOAT *enn = &psv->en[chn].l[0];
|
||
|
FLOAT *thm = &psv->thm[chn].l[0];
|
||
|
convert_partition2scalefac(gdl, eb, thr, enn, thm);
|
||
|
}
|
||
|
|
||
|
static void
|
||
|
convert_partition2scalefac_l_to_s(lame_internal_flags * gfc, FLOAT const *eb, FLOAT const *thr,
|
||
|
int chn)
|
||
|
{
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_CB2SB_t const *const gds = &gfc->cd_psy->l_to_s;
|
||
|
FLOAT enn[SBMAX_s], thm[SBMAX_s];
|
||
|
int sb, sblock;
|
||
|
convert_partition2scalefac(gds, eb, thr, enn, thm);
|
||
|
for (sb = 0; sb < SBMAX_s; ++sb) {
|
||
|
FLOAT const scale = 1. / 64.f;
|
||
|
FLOAT const tmp_enn = enn[sb];
|
||
|
FLOAT const tmp_thm = thm[sb] * scale;
|
||
|
for (sblock = 0; sblock < 3; ++sblock) {
|
||
|
psv->en[chn].s[sb][sblock] = tmp_enn;
|
||
|
psv->thm[chn].s[sb][sblock] = tmp_thm;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
static inline FLOAT
|
||
|
NS_INTERP(FLOAT x, FLOAT y, FLOAT r)
|
||
|
{
|
||
|
/* was pow((x),(r))*pow((y),1-(r)) */
|
||
|
if (r >= 1.0f)
|
||
|
return x; /* 99.7% of the time */
|
||
|
if (r <= 0.0f)
|
||
|
return y;
|
||
|
if (y > 0.0f)
|
||
|
return powf(x / y, r) * y; /* rest of the time */
|
||
|
return 0.0f; /* never happens */
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
static FLOAT
|
||
|
pecalc_s(III_psy_ratio const *mr, FLOAT masking_lower)
|
||
|
{
|
||
|
FLOAT pe_s;
|
||
|
static const FLOAT regcoef_s[] = {
|
||
|
11.8, /* these values are tuned only for 44.1kHz... */
|
||
|
13.6,
|
||
|
17.2,
|
||
|
32,
|
||
|
46.5,
|
||
|
51.3,
|
||
|
57.5,
|
||
|
67.1,
|
||
|
71.5,
|
||
|
84.6,
|
||
|
97.6,
|
||
|
130,
|
||
|
/* 255.8 */
|
||
|
};
|
||
|
unsigned int sb, sblock;
|
||
|
|
||
|
pe_s = 1236.28f / 4;
|
||
|
for (sb = 0; sb < SBMAX_s - 1; sb++) {
|
||
|
for (sblock = 0; sblock < 3; sblock++) {
|
||
|
FLOAT const thm = mr->thm.s[sb][sblock];
|
||
|
assert(sb < dimension_of(regcoef_s));
|
||
|
if (thm > 0.0f) {
|
||
|
FLOAT const x = thm * masking_lower;
|
||
|
FLOAT const en = mr->en.s[sb][sblock];
|
||
|
if (en > x) {
|
||
|
if (en > x * 1e10f) {
|
||
|
pe_s += regcoef_s[sb] * (10.0f * LOG10);
|
||
|
}
|
||
|
else {
|
||
|
assert(x > 0);
|
||
|
pe_s += regcoef_s[sb] * FAST_LOG10(en / x);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return pe_s;
|
||
|
}
|
||
|
|
||
|
static FLOAT
|
||
|
pecalc_l(III_psy_ratio const *mr, FLOAT masking_lower)
|
||
|
{
|
||
|
FLOAT pe_l;
|
||
|
static const FLOAT regcoef_l[] = {
|
||
|
6.8, /* these values are tuned only for 44.1kHz... */
|
||
|
5.8,
|
||
|
5.8,
|
||
|
6.4,
|
||
|
6.5,
|
||
|
9.9,
|
||
|
12.1,
|
||
|
14.4,
|
||
|
15,
|
||
|
18.9,
|
||
|
21.6,
|
||
|
26.9,
|
||
|
34.2,
|
||
|
40.2,
|
||
|
46.8,
|
||
|
56.5,
|
||
|
60.7,
|
||
|
73.9,
|
||
|
85.7,
|
||
|
93.4,
|
||
|
126.1,
|
||
|
/* 241.3 */
|
||
|
};
|
||
|
unsigned int sb;
|
||
|
|
||
|
pe_l = 1124.23f / 4;
|
||
|
for (sb = 0; sb < SBMAX_l - 1; sb++) {
|
||
|
FLOAT const thm = mr->thm.l[sb];
|
||
|
assert(sb < dimension_of(regcoef_l));
|
||
|
if (thm > 0.0f) {
|
||
|
FLOAT const x = thm * masking_lower;
|
||
|
FLOAT const en = mr->en.l[sb];
|
||
|
if (en > x) {
|
||
|
if (en > x * 1e10f) {
|
||
|
pe_l += regcoef_l[sb] * (10.0f * LOG10);
|
||
|
}
|
||
|
else {
|
||
|
assert(x > 0);
|
||
|
pe_l += regcoef_l[sb] * FAST_LOG10(en / x);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return pe_l;
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
calc_energy(PsyConst_CB2SB_t const *l, FLOAT const *fftenergy, FLOAT * eb, FLOAT * max, FLOAT * avg)
|
||
|
{
|
||
|
int b, j;
|
||
|
|
||
|
for (b = j = 0; b < l->npart; ++b) {
|
||
|
FLOAT ebb = 0, m = 0;
|
||
|
int i;
|
||
|
for (i = 0; i < l->numlines[b]; ++i, ++j) {
|
||
|
FLOAT const el = fftenergy[j];
|
||
|
assert(el >= 0);
|
||
|
ebb += el;
|
||
|
if (m < el)
|
||
|
m = el;
|
||
|
}
|
||
|
eb[b] = ebb;
|
||
|
max[b] = m;
|
||
|
avg[b] = ebb * l->rnumlines[b];
|
||
|
assert(l->rnumlines[b] >= 0);
|
||
|
assert(ebb >= 0);
|
||
|
assert(eb[b] >= 0);
|
||
|
assert(max[b] >= 0);
|
||
|
assert(avg[b] >= 0);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
calc_mask_index_l(lame_internal_flags const *gfc, FLOAT const *max,
|
||
|
FLOAT const *avg, unsigned char *mask_idx)
|
||
|
{
|
||
|
PsyConst_CB2SB_t const *const gdl = &gfc->cd_psy->l;
|
||
|
FLOAT m, a;
|
||
|
int b, k;
|
||
|
int const last_tab_entry = sizeof(tab) / sizeof(tab[0]) - 1;
|
||
|
b = 0;
|
||
|
a = avg[b] + avg[b + 1];
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0f) {
|
||
|
m = max[b];
|
||
|
if (m < max[b + 1])
|
||
|
m = max[b + 1];
|
||
|
assert((gdl->numlines[b] + gdl->numlines[b + 1] - 1) > 0);
|
||
|
a = 20.0f * (m * 2.0f - a)
|
||
|
/ (a * (gdl->numlines[b] + gdl->numlines[b + 1] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
|
||
|
for (b = 1; b < gdl->npart - 1; b++) {
|
||
|
a = avg[b - 1] + avg[b] + avg[b + 1];
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0f) {
|
||
|
m = max[b - 1];
|
||
|
if (m < max[b])
|
||
|
m = max[b];
|
||
|
if (m < max[b + 1])
|
||
|
m = max[b + 1];
|
||
|
assert((gdl->numlines[b - 1] + gdl->numlines[b] + gdl->numlines[b + 1] - 1) > 0);
|
||
|
a = 20.0f * (m * 3.0f - a)
|
||
|
/ (a * (gdl->numlines[b - 1] + gdl->numlines[b] + gdl->numlines[b + 1] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
}
|
||
|
assert(b > 0);
|
||
|
assert(b == gdl->npart - 1);
|
||
|
|
||
|
a = avg[b - 1] + avg[b];
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0f) {
|
||
|
m = max[b - 1];
|
||
|
if (m < max[b])
|
||
|
m = max[b];
|
||
|
assert((gdl->numlines[b - 1] + gdl->numlines[b] - 1) > 0);
|
||
|
a = 20.0f * (m * 2.0f - a)
|
||
|
/ (a * (gdl->numlines[b - 1] + gdl->numlines[b] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
assert(b == (gdl->npart - 1));
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_fft_l(lame_internal_flags * gfc, const sample_t * const buffer[2], int chn,
|
||
|
int gr_out, FLOAT fftenergy[HBLKSIZE], FLOAT(*wsamp_l)[BLKSIZE])
|
||
|
{
|
||
|
SessionConfig_t const *const cfg = &gfc->cfg;
|
||
|
PsyStateVar_t *psv = &gfc->sv_psy;
|
||
|
plotting_data *plt = cfg->analysis ? gfc->pinfo : 0;
|
||
|
int j;
|
||
|
|
||
|
if (chn < 2) {
|
||
|
fft_long(gfc, *wsamp_l, chn, buffer);
|
||
|
}
|
||
|
else if (chn == 2) {
|
||
|
FLOAT const sqrt2_half = SQRT2 * 0.5f;
|
||
|
/* FFT data for mid and side channel is derived from L & R */
|
||
|
for (j = BLKSIZE - 1; j >= 0; --j) {
|
||
|
FLOAT const l = wsamp_l[0][j];
|
||
|
FLOAT const r = wsamp_l[1][j];
|
||
|
wsamp_l[0][j] = (l + r) * sqrt2_half;
|
||
|
wsamp_l[1][j] = (l - r) * sqrt2_half;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/*********************************************************************
|
||
|
* compute energies
|
||
|
*********************************************************************/
|
||
|
fftenergy[0] = wsamp_l[0][0];
|
||
|
fftenergy[0] *= fftenergy[0];
|
||
|
|
||
|
for (j = BLKSIZE / 2 - 1; j >= 0; --j) {
|
||
|
FLOAT const re = (*wsamp_l)[BLKSIZE / 2 - j];
|
||
|
FLOAT const im = (*wsamp_l)[BLKSIZE / 2 + j];
|
||
|
fftenergy[BLKSIZE / 2 - j] = (re * re + im * im) * 0.5f;
|
||
|
}
|
||
|
/* total energy */
|
||
|
{
|
||
|
FLOAT totalenergy = 0.0f;
|
||
|
for (j = 11; j < HBLKSIZE; j++)
|
||
|
totalenergy += fftenergy[j];
|
||
|
|
||
|
psv->tot_ener[chn] = totalenergy;
|
||
|
}
|
||
|
|
||
|
if (plt) {
|
||
|
for (j = 0; j < HBLKSIZE; j++) {
|
||
|
plt->energy[gr_out][chn][j] = plt->energy_save[chn][j];
|
||
|
plt->energy_save[chn][j] = fftenergy[j];
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_fft_s(lame_internal_flags const *gfc, const sample_t * const buffer[2], int chn,
|
||
|
int sblock, FLOAT(*fftenergy_s)[HBLKSIZE_s], FLOAT(*wsamp_s)[3][BLKSIZE_s])
|
||
|
{
|
||
|
int j;
|
||
|
|
||
|
if (sblock == 0 && chn < 2) {
|
||
|
fft_short(gfc, *wsamp_s, chn, buffer);
|
||
|
}
|
||
|
if (chn == 2) {
|
||
|
FLOAT const sqrt2_half = SQRT2 * 0.5f;
|
||
|
/* FFT data for mid and side channel is derived from L & R */
|
||
|
for (j = BLKSIZE_s - 1; j >= 0; --j) {
|
||
|
FLOAT const l = wsamp_s[0][sblock][j];
|
||
|
FLOAT const r = wsamp_s[1][sblock][j];
|
||
|
wsamp_s[0][sblock][j] = (l + r) * sqrt2_half;
|
||
|
wsamp_s[1][sblock][j] = (l - r) * sqrt2_half;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/*********************************************************************
|
||
|
* compute energies
|
||
|
*********************************************************************/
|
||
|
fftenergy_s[sblock][0] = (*wsamp_s)[sblock][0];
|
||
|
fftenergy_s[sblock][0] *= fftenergy_s[sblock][0];
|
||
|
for (j = BLKSIZE_s / 2 - 1; j >= 0; --j) {
|
||
|
FLOAT const re = (*wsamp_s)[sblock][BLKSIZE_s / 2 - j];
|
||
|
FLOAT const im = (*wsamp_s)[sblock][BLKSIZE_s / 2 + j];
|
||
|
fftenergy_s[sblock][BLKSIZE_s / 2 - j] = (re * re + im * im) * 0.5f;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
/*********************************************************************
|
||
|
* compute loudness approximation (used for ATH auto-level adjustment)
|
||
|
*********************************************************************/
|
||
|
static void
|
||
|
vbrpsy_compute_loudness_approximation_l(lame_internal_flags * gfc, int gr_out, int chn,
|
||
|
const FLOAT fftenergy[HBLKSIZE])
|
||
|
{
|
||
|
PsyStateVar_t *psv = &gfc->sv_psy;
|
||
|
if (chn < 2) { /*no loudness for mid/side ch */
|
||
|
gfc->ov_psy.loudness_sq[gr_out][chn] = psv->loudness_sq_save[chn];
|
||
|
psv->loudness_sq_save[chn] = psycho_loudness_approx(fftenergy, gfc->ATH->eql_w);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
/**********************************************************************
|
||
|
* Apply HPF of fs/4 to the input signal.
|
||
|
* This is used for attack detection / handling.
|
||
|
**********************************************************************/
|
||
|
static void
|
||
|
vbrpsy_attack_detection(lame_internal_flags * gfc, const sample_t * const buffer[2], int gr_out,
|
||
|
III_psy_ratio masking_ratio[2][2], III_psy_ratio masking_MS_ratio[2][2],
|
||
|
FLOAT energy[4], FLOAT sub_short_factor[4][3], int ns_attacks[4][4],
|
||
|
int uselongblock[2])
|
||
|
{
|
||
|
FLOAT ns_hpfsmpl[2][576];
|
||
|
SessionConfig_t const *const cfg = &gfc->cfg;
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
plotting_data *plt = cfg->analysis ? gfc->pinfo : 0;
|
||
|
int const n_chn_out = cfg->channels_out;
|
||
|
/* chn=2 and 3 = Mid and Side channels */
|
||
|
int const n_chn_psy = (cfg->mode == JOINT_STEREO) ? 4 : n_chn_out;
|
||
|
int chn, i, j;
|
||
|
|
||
|
memset(&ns_hpfsmpl[0][0], 0, sizeof(ns_hpfsmpl));
|
||
|
/* Don't copy the input buffer into a temporary buffer */
|
||
|
/* unroll the loop 2 times */
|
||
|
for (chn = 0; chn < n_chn_out; chn++) {
|
||
|
static const FLOAT fircoef[] = {
|
||
|
-8.65163e-18 * 2, -0.00851586 * 2, -6.74764e-18 * 2, 0.0209036 * 2,
|
||
|
-3.36639e-17 * 2, -0.0438162 * 2, -1.54175e-17 * 2, 0.0931738 * 2,
|
||
|
-5.52212e-17 * 2, -0.313819 * 2
|
||
|
};
|
||
|
/* apply high pass filter of fs/4 */
|
||
|
const sample_t *const firbuf = &buffer[chn][576 - 350 - NSFIRLEN + 192];
|
||
|
assert(dimension_of(fircoef) == ((NSFIRLEN - 1) / 2));
|
||
|
for (i = 0; i < 576; i++) {
|
||
|
FLOAT sum1, sum2;
|
||
|
sum1 = firbuf[i + 10];
|
||
|
sum2 = 0.0;
|
||
|
for (j = 0; j < ((NSFIRLEN - 1) / 2) - 1; j += 2) {
|
||
|
sum1 += fircoef[j] * (firbuf[i + j] + firbuf[i + NSFIRLEN - j]);
|
||
|
sum2 += fircoef[j + 1] * (firbuf[i + j + 1] + firbuf[i + NSFIRLEN - j - 1]);
|
||
|
}
|
||
|
ns_hpfsmpl[chn][i] = sum1 + sum2;
|
||
|
}
|
||
|
masking_ratio[gr_out][chn].en = psv->en[chn];
|
||
|
masking_ratio[gr_out][chn].thm = psv->thm[chn];
|
||
|
if (n_chn_psy > 2) {
|
||
|
/* MS maskings */
|
||
|
/*percep_MS_entropy [chn-2] = gfc -> pe [chn]; */
|
||
|
masking_MS_ratio[gr_out][chn].en = psv->en[chn + 2];
|
||
|
masking_MS_ratio[gr_out][chn].thm = psv->thm[chn + 2];
|
||
|
}
|
||
|
}
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
FLOAT attack_intensity[12];
|
||
|
FLOAT en_subshort[12];
|
||
|
FLOAT en_short[4] = { 0, 0, 0, 0 };
|
||
|
FLOAT const *pf = ns_hpfsmpl[chn & 1];
|
||
|
int ns_uselongblock = 1;
|
||
|
|
||
|
if (chn == 2) {
|
||
|
for (i = 0, j = 576; j > 0; ++i, --j) {
|
||
|
FLOAT const l = ns_hpfsmpl[0][i];
|
||
|
FLOAT const r = ns_hpfsmpl[1][i];
|
||
|
ns_hpfsmpl[0][i] = l + r;
|
||
|
ns_hpfsmpl[1][i] = l - r;
|
||
|
}
|
||
|
}
|
||
|
/***************************************************************
|
||
|
* determine the block type (window type)
|
||
|
***************************************************************/
|
||
|
/* calculate energies of each sub-shortblocks */
|
||
|
for (i = 0; i < 3; i++) {
|
||
|
en_subshort[i] = psv->last_en_subshort[chn][i + 6];
|
||
|
assert(psv->last_en_subshort[chn][i + 4] > 0);
|
||
|
attack_intensity[i] = en_subshort[i] / psv->last_en_subshort[chn][i + 4];
|
||
|
en_short[0] += en_subshort[i];
|
||
|
}
|
||
|
|
||
|
for (i = 0; i < 9; i++) {
|
||
|
FLOAT const *const pfe = pf + 576 / 9;
|
||
|
FLOAT p = 1.;
|
||
|
for (; pf < pfe; pf++)
|
||
|
if (p < fabs(*pf))
|
||
|
p = fabs(*pf);
|
||
|
psv->last_en_subshort[chn][i] = en_subshort[i + 3] = p;
|
||
|
en_short[1 + i / 3] += p;
|
||
|
if (p > en_subshort[i + 3 - 2]) {
|
||
|
assert(en_subshort[i + 3 - 2] > 0);
|
||
|
p = p / en_subshort[i + 3 - 2];
|
||
|
}
|
||
|
else if (en_subshort[i + 3 - 2] > p * 10.0f) {
|
||
|
assert(p > 0);
|
||
|
p = en_subshort[i + 3 - 2] / (p * 10.0f);
|
||
|
}
|
||
|
else {
|
||
|
p = 0.0;
|
||
|
}
|
||
|
attack_intensity[i + 3] = p;
|
||
|
}
|
||
|
|
||
|
/* pulse like signal detection for fatboy.wav and so on */
|
||
|
for (i = 0; i < 3; ++i) {
|
||
|
FLOAT const enn =
|
||
|
en_subshort[i * 3 + 3] + en_subshort[i * 3 + 4] + en_subshort[i * 3 + 5];
|
||
|
FLOAT factor = 1.f;
|
||
|
if (en_subshort[i * 3 + 5] * 6 < enn) {
|
||
|
factor *= 0.5f;
|
||
|
if (en_subshort[i * 3 + 4] * 6 < enn) {
|
||
|
factor *= 0.5f;
|
||
|
}
|
||
|
}
|
||
|
sub_short_factor[chn][i] = factor;
|
||
|
}
|
||
|
|
||
|
if (plt) {
|
||
|
FLOAT x = attack_intensity[0];
|
||
|
for (i = 1; i < 12; i++) {
|
||
|
if (x < attack_intensity[i]) {
|
||
|
x = attack_intensity[i];
|
||
|
}
|
||
|
}
|
||
|
plt->ers[gr_out][chn] = plt->ers_save[chn];
|
||
|
plt->ers_save[chn] = x;
|
||
|
}
|
||
|
|
||
|
/* compare energies between sub-shortblocks */
|
||
|
{
|
||
|
FLOAT x = gfc->cd_psy->attack_threshold[chn];
|
||
|
for (i = 0; i < 12; i++) {
|
||
|
if (ns_attacks[chn][i / 3] == 0) {
|
||
|
if (attack_intensity[i] > x) {
|
||
|
ns_attacks[chn][i / 3] = (i % 3) + 1;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
/* should have energy change between short blocks, in order to avoid periodic signals */
|
||
|
/* Good samples to show the effect are Trumpet test songs */
|
||
|
/* GB: tuned (1) to avoid too many short blocks for test sample TRUMPET */
|
||
|
/* RH: tuned (2) to let enough short blocks through for test sample FSOL and SNAPS */
|
||
|
for (i = 1; i < 4; i++) {
|
||
|
FLOAT const u = en_short[i - 1];
|
||
|
FLOAT const v = en_short[i];
|
||
|
FLOAT const m = Max(u, v);
|
||
|
if (m < 40000) { /* (2) */
|
||
|
if (u < 1.7f * v && v < 1.7f * u) { /* (1) */
|
||
|
if (i == 1 && ns_attacks[chn][0] <= ns_attacks[chn][i]) {
|
||
|
ns_attacks[chn][0] = 0;
|
||
|
}
|
||
|
ns_attacks[chn][i] = 0;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if (ns_attacks[chn][0] <= psv->last_attacks[chn]) {
|
||
|
ns_attacks[chn][0] = 0;
|
||
|
}
|
||
|
|
||
|
if (psv->last_attacks[chn] == 3 ||
|
||
|
ns_attacks[chn][0] + ns_attacks[chn][1] + ns_attacks[chn][2] + ns_attacks[chn][3]) {
|
||
|
ns_uselongblock = 0;
|
||
|
|
||
|
if (ns_attacks[chn][1] && ns_attacks[chn][0]) {
|
||
|
ns_attacks[chn][1] = 0;
|
||
|
}
|
||
|
if (ns_attacks[chn][2] && ns_attacks[chn][1]) {
|
||
|
ns_attacks[chn][2] = 0;
|
||
|
}
|
||
|
if (ns_attacks[chn][3] && ns_attacks[chn][2]) {
|
||
|
ns_attacks[chn][3] = 0;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if (chn < 2) {
|
||
|
uselongblock[chn] = ns_uselongblock;
|
||
|
}
|
||
|
else {
|
||
|
if (ns_uselongblock == 0) {
|
||
|
uselongblock[0] = uselongblock[1] = 0;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/* there is a one granule delay. Copy maskings computed last call
|
||
|
* into masking_ratio to return to calling program.
|
||
|
*/
|
||
|
energy[chn] = psv->tot_ener[chn];
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_skip_masking_s(lame_internal_flags * gfc, int chn, int sblock)
|
||
|
{
|
||
|
if (sblock == 0) {
|
||
|
FLOAT *nbs2 = &gfc->sv_psy.nb_s2[chn][0];
|
||
|
FLOAT *nbs1 = &gfc->sv_psy.nb_s1[chn][0];
|
||
|
int const n = gfc->cd_psy->s.npart;
|
||
|
int b;
|
||
|
for (b = 0; b < n; b++) {
|
||
|
nbs2[b] = nbs1[b];
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_calc_mask_index_s(lame_internal_flags const *gfc, FLOAT const *max,
|
||
|
FLOAT const *avg, unsigned char *mask_idx)
|
||
|
{
|
||
|
PsyConst_CB2SB_t const *const gds = &gfc->cd_psy->s;
|
||
|
FLOAT m, a;
|
||
|
int b, k;
|
||
|
int const last_tab_entry = dimension_of(tab) - 1;
|
||
|
b = 0;
|
||
|
a = avg[b] + avg[b + 1];
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0f) {
|
||
|
m = max[b];
|
||
|
if (m < max[b + 1])
|
||
|
m = max[b + 1];
|
||
|
assert((gds->numlines[b] + gds->numlines[b + 1] - 1) > 0);
|
||
|
a = 20.0f * (m * 2.0f - a)
|
||
|
/ (a * (gds->numlines[b] + gds->numlines[b + 1] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
|
||
|
for (b = 1; b < gds->npart - 1; b++) {
|
||
|
a = avg[b - 1] + avg[b] + avg[b + 1];
|
||
|
assert(b + 1 < gds->npart);
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0) {
|
||
|
m = max[b - 1];
|
||
|
if (m < max[b])
|
||
|
m = max[b];
|
||
|
if (m < max[b + 1])
|
||
|
m = max[b + 1];
|
||
|
assert((gds->numlines[b - 1] + gds->numlines[b] + gds->numlines[b + 1] - 1) > 0);
|
||
|
a = 20.0f * (m * 3.0f - a)
|
||
|
/ (a * (gds->numlines[b - 1] + gds->numlines[b] + gds->numlines[b + 1] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
}
|
||
|
assert(b > 0);
|
||
|
assert(b == gds->npart - 1);
|
||
|
|
||
|
a = avg[b - 1] + avg[b];
|
||
|
assert(a >= 0);
|
||
|
if (a > 0.0f) {
|
||
|
m = max[b - 1];
|
||
|
if (m < max[b])
|
||
|
m = max[b];
|
||
|
assert((gds->numlines[b - 1] + gds->numlines[b] - 1) > 0);
|
||
|
a = 20.0f * (m * 2.0f - a)
|
||
|
/ (a * (gds->numlines[b - 1] + gds->numlines[b] - 1));
|
||
|
k = (int) a;
|
||
|
if (k > last_tab_entry)
|
||
|
k = last_tab_entry;
|
||
|
mask_idx[b] = k;
|
||
|
}
|
||
|
else {
|
||
|
mask_idx[b] = 0;
|
||
|
}
|
||
|
assert(b == (gds->npart - 1));
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_masking_s(lame_internal_flags * gfc, const FLOAT(*fftenergy_s)[HBLKSIZE_s],
|
||
|
FLOAT * eb, FLOAT * thr, int chn, int sblock)
|
||
|
{
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_CB2SB_t const *const gds = &gfc->cd_psy->s;
|
||
|
FLOAT max[CBANDS], avg[CBANDS];
|
||
|
int i, j, b;
|
||
|
unsigned char mask_idx_s[CBANDS];
|
||
|
|
||
|
memset(max, 0, sizeof(max));
|
||
|
memset(avg, 0, sizeof(avg));
|
||
|
|
||
|
for (b = j = 0; b < gds->npart; ++b) {
|
||
|
FLOAT ebb = 0, m = 0;
|
||
|
int const n = gds->numlines[b];
|
||
|
for (i = 0; i < n; ++i, ++j) {
|
||
|
FLOAT const el = fftenergy_s[sblock][j];
|
||
|
ebb += el;
|
||
|
if (m < el)
|
||
|
m = el;
|
||
|
}
|
||
|
eb[b] = ebb;
|
||
|
assert(ebb >= 0);
|
||
|
max[b] = m;
|
||
|
assert(n > 0);
|
||
|
avg[b] = ebb * gds->rnumlines[b];
|
||
|
assert(avg[b] >= 0);
|
||
|
}
|
||
|
assert(b == gds->npart);
|
||
|
assert(j == 129);
|
||
|
vbrpsy_calc_mask_index_s(gfc, max, avg, mask_idx_s);
|
||
|
for (j = b = 0; b < gds->npart; b++) {
|
||
|
int kk = gds->s3ind[b][0];
|
||
|
int const last = gds->s3ind[b][1];
|
||
|
int const delta = mask_add_delta(mask_idx_s[b]);
|
||
|
int dd, dd_n;
|
||
|
FLOAT x, ecb, avg_mask;
|
||
|
FLOAT const masking_lower = gds->masking_lower[b] * gfc->sv_qnt.masking_lower;
|
||
|
|
||
|
dd = mask_idx_s[kk];
|
||
|
dd_n = 1;
|
||
|
ecb = gds->s3[j] * eb[kk] * tab[mask_idx_s[kk]];
|
||
|
++j, ++kk;
|
||
|
while (kk <= last) {
|
||
|
dd += mask_idx_s[kk];
|
||
|
dd_n += 1;
|
||
|
x = gds->s3[j] * eb[kk] * tab[mask_idx_s[kk]];
|
||
|
ecb = vbrpsy_mask_add(ecb, x, kk - b, delta);
|
||
|
++j, ++kk;
|
||
|
}
|
||
|
dd = (1 + 2 * dd) / (2 * dd_n);
|
||
|
avg_mask = tab[dd] * 0.5f;
|
||
|
ecb *= avg_mask;
|
||
|
#if 0 /* we can do PRE ECHO control now here, or do it later */
|
||
|
if (psv->blocktype_old[chn & 0x01] == SHORT_TYPE) {
|
||
|
/* limit calculated threshold by even older granule */
|
||
|
FLOAT const t1 = rpelev_s * psv->nb_s1[chn][b];
|
||
|
FLOAT const t2 = rpelev2_s * psv->nb_s2[chn][b];
|
||
|
FLOAT const tm = (t2 > 0) ? Min(ecb, t2) : ecb;
|
||
|
thr[b] = (t1 > 0) ? NS_INTERP(Min(tm, t1), ecb, 0.6) : ecb;
|
||
|
}
|
||
|
else {
|
||
|
/* limit calculated threshold by older granule */
|
||
|
FLOAT const t1 = rpelev_s * psv->nb_s1[chn][b];
|
||
|
thr[b] = (t1 > 0) ? NS_INTERP(Min(ecb, t1), ecb, 0.6) : ecb;
|
||
|
}
|
||
|
#else /* we do it later */
|
||
|
thr[b] = ecb;
|
||
|
#endif
|
||
|
psv->nb_s2[chn][b] = psv->nb_s1[chn][b];
|
||
|
psv->nb_s1[chn][b] = ecb;
|
||
|
{
|
||
|
/* if THR exceeds EB, the quantization routines will take the difference
|
||
|
* from other bands. in case of strong tonal samples (tonaltest.wav)
|
||
|
* this leads to heavy distortions. that's why we limit THR here.
|
||
|
*/
|
||
|
x = max[b];
|
||
|
x *= gds->minval[b];
|
||
|
x *= avg_mask;
|
||
|
if (thr[b] > x) {
|
||
|
thr[b] = x;
|
||
|
}
|
||
|
}
|
||
|
if (masking_lower > 1) {
|
||
|
thr[b] *= masking_lower;
|
||
|
}
|
||
|
if (thr[b] > eb[b]) {
|
||
|
thr[b] = eb[b];
|
||
|
}
|
||
|
if (masking_lower < 1) {
|
||
|
thr[b] *= masking_lower;
|
||
|
}
|
||
|
|
||
|
assert(thr[b] >= 0);
|
||
|
}
|
||
|
for (; b < CBANDS; ++b) {
|
||
|
eb[b] = 0;
|
||
|
thr[b] = 0;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_masking_l(lame_internal_flags * gfc, const FLOAT fftenergy[HBLKSIZE],
|
||
|
FLOAT eb_l[CBANDS], FLOAT thr[CBANDS], int chn)
|
||
|
{
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_CB2SB_t const *const gdl = &gfc->cd_psy->l;
|
||
|
FLOAT max[CBANDS], avg[CBANDS];
|
||
|
unsigned char mask_idx_l[CBANDS + 2];
|
||
|
int k, b;
|
||
|
|
||
|
/*********************************************************************
|
||
|
* Calculate the energy and the tonality of each partition.
|
||
|
*********************************************************************/
|
||
|
calc_energy(gdl, fftenergy, eb_l, max, avg);
|
||
|
calc_mask_index_l(gfc, max, avg, mask_idx_l);
|
||
|
|
||
|
/*********************************************************************
|
||
|
* convolve the partitioned energy and unpredictability
|
||
|
* with the spreading function, s3_l[b][k]
|
||
|
********************************************************************/
|
||
|
k = 0;
|
||
|
for (b = 0; b < gdl->npart; b++) {
|
||
|
FLOAT x, ecb, avg_mask, t;
|
||
|
FLOAT const masking_lower = gdl->masking_lower[b] * gfc->sv_qnt.masking_lower;
|
||
|
/* convolve the partitioned energy with the spreading function */
|
||
|
int kk = gdl->s3ind[b][0];
|
||
|
int const last = gdl->s3ind[b][1];
|
||
|
int const delta = mask_add_delta(mask_idx_l[b]);
|
||
|
int dd = 0, dd_n = 0;
|
||
|
|
||
|
dd = mask_idx_l[kk];
|
||
|
dd_n += 1;
|
||
|
ecb = gdl->s3[k] * eb_l[kk] * tab[mask_idx_l[kk]];
|
||
|
++k, ++kk;
|
||
|
while (kk <= last) {
|
||
|
dd += mask_idx_l[kk];
|
||
|
dd_n += 1;
|
||
|
x = gdl->s3[k] * eb_l[kk] * tab[mask_idx_l[kk]];
|
||
|
t = vbrpsy_mask_add(ecb, x, kk - b, delta);
|
||
|
#if 0
|
||
|
ecb += eb_l[kk];
|
||
|
if (ecb > t) {
|
||
|
ecb = t;
|
||
|
}
|
||
|
#else
|
||
|
ecb = t;
|
||
|
#endif
|
||
|
++k, ++kk;
|
||
|
}
|
||
|
dd = (1 + 2 * dd) / (2 * dd_n);
|
||
|
avg_mask = tab[dd] * 0.5f;
|
||
|
ecb *= avg_mask;
|
||
|
|
||
|
/**** long block pre-echo control ****/
|
||
|
/* dont use long block pre-echo control if previous granule was
|
||
|
* a short block. This is to avoid the situation:
|
||
|
* frame0: quiet (very low masking)
|
||
|
* frame1: surge (triggers short blocks)
|
||
|
* frame2: regular frame. looks like pre-echo when compared to
|
||
|
* frame0, but all pre-echo was in frame1.
|
||
|
*/
|
||
|
/* chn=0,1 L and R channels
|
||
|
chn=2,3 S and M channels.
|
||
|
*/
|
||
|
if (psv->blocktype_old[chn & 0x01] == SHORT_TYPE) {
|
||
|
FLOAT const ecb_limit = rpelev * psv->nb_l1[chn][b];
|
||
|
if (ecb_limit > 0) {
|
||
|
thr[b] = Min(ecb, ecb_limit);
|
||
|
}
|
||
|
else {
|
||
|
/* Robert 071209:
|
||
|
Because we don't calculate long block psy when we know a granule
|
||
|
should be of short blocks, we don't have any clue how the granule
|
||
|
before would have looked like as a long block. So we have to guess
|
||
|
a little bit for this END_TYPE block.
|
||
|
Most of the time we get away with this sloppyness. (fingers crossed :)
|
||
|
The speed increase is worth it.
|
||
|
*/
|
||
|
thr[b] = Min(ecb, eb_l[b] * NS_PREECHO_ATT2);
|
||
|
}
|
||
|
}
|
||
|
else {
|
||
|
FLOAT ecb_limit_2 = rpelev2 * psv->nb_l2[chn][b];
|
||
|
FLOAT ecb_limit_1 = rpelev * psv->nb_l1[chn][b];
|
||
|
FLOAT ecb_limit;
|
||
|
if (ecb_limit_2 <= 0) {
|
||
|
ecb_limit_2 = ecb;
|
||
|
}
|
||
|
if (ecb_limit_1 <= 0) {
|
||
|
ecb_limit_1 = ecb;
|
||
|
}
|
||
|
if (psv->blocktype_old[chn & 0x01] == NORM_TYPE) {
|
||
|
ecb_limit = Min(ecb_limit_1, ecb_limit_2);
|
||
|
}
|
||
|
else {
|
||
|
ecb_limit = ecb_limit_1;
|
||
|
}
|
||
|
thr[b] = Min(ecb, ecb_limit);
|
||
|
}
|
||
|
psv->nb_l2[chn][b] = psv->nb_l1[chn][b];
|
||
|
psv->nb_l1[chn][b] = ecb;
|
||
|
{
|
||
|
/* if THR exceeds EB, the quantization routines will take the difference
|
||
|
* from other bands. in case of strong tonal samples (tonaltest.wav)
|
||
|
* this leads to heavy distortions. that's why we limit THR here.
|
||
|
*/
|
||
|
x = max[b];
|
||
|
x *= gdl->minval[b];
|
||
|
x *= avg_mask;
|
||
|
if (thr[b] > x) {
|
||
|
thr[b] = x;
|
||
|
}
|
||
|
}
|
||
|
if (masking_lower > 1) {
|
||
|
thr[b] *= masking_lower;
|
||
|
}
|
||
|
if (thr[b] > eb_l[b]) {
|
||
|
thr[b] = eb_l[b];
|
||
|
}
|
||
|
if (masking_lower < 1) {
|
||
|
thr[b] *= masking_lower;
|
||
|
}
|
||
|
assert(thr[b] >= 0);
|
||
|
}
|
||
|
for (; b < CBANDS; ++b) {
|
||
|
eb_l[b] = 0;
|
||
|
thr[b] = 0;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_block_type(SessionConfig_t const *cfg, int *uselongblock)
|
||
|
{
|
||
|
int chn;
|
||
|
|
||
|
if (cfg->short_blocks == short_block_coupled
|
||
|
/* force both channels to use the same block type */
|
||
|
/* this is necessary if the frame is to be encoded in ms_stereo. */
|
||
|
/* But even without ms_stereo, FhG does this */
|
||
|
&& !(uselongblock[0] && uselongblock[1]))
|
||
|
uselongblock[0] = uselongblock[1] = 0;
|
||
|
|
||
|
for (chn = 0; chn < cfg->channels_out; chn++) {
|
||
|
/* disable short blocks */
|
||
|
if (cfg->short_blocks == short_block_dispensed) {
|
||
|
uselongblock[chn] = 1;
|
||
|
}
|
||
|
if (cfg->short_blocks == short_block_forced) {
|
||
|
uselongblock[chn] = 0;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
static void
|
||
|
vbrpsy_apply_block_type(PsyStateVar_t * psv, int nch, int const *uselongblock, int *blocktype_d)
|
||
|
{
|
||
|
int chn;
|
||
|
|
||
|
/* update the blocktype of the previous granule, since it depends on what
|
||
|
* happend in this granule */
|
||
|
for (chn = 0; chn < nch; chn++) {
|
||
|
int blocktype = NORM_TYPE;
|
||
|
/* disable short blocks */
|
||
|
|
||
|
if (uselongblock[chn]) {
|
||
|
/* no attack : use long blocks */
|
||
|
assert(psv->blocktype_old[chn] != START_TYPE);
|
||
|
if (psv->blocktype_old[chn] == SHORT_TYPE)
|
||
|
blocktype = STOP_TYPE;
|
||
|
}
|
||
|
else {
|
||
|
/* attack : use short blocks */
|
||
|
blocktype = SHORT_TYPE;
|
||
|
if (psv->blocktype_old[chn] == NORM_TYPE) {
|
||
|
psv->blocktype_old[chn] = START_TYPE;
|
||
|
}
|
||
|
if (psv->blocktype_old[chn] == STOP_TYPE)
|
||
|
psv->blocktype_old[chn] = SHORT_TYPE;
|
||
|
}
|
||
|
|
||
|
blocktype_d[chn] = psv->blocktype_old[chn]; /* value returned to calling program */
|
||
|
psv->blocktype_old[chn] = blocktype; /* save for next call to l3psy_anal */
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
/***************************************************************
|
||
|
* compute M/S thresholds from Johnston & Ferreira 1992 ICASSP paper
|
||
|
***************************************************************/
|
||
|
|
||
|
static void
|
||
|
vbrpsy_compute_MS_thresholds(const FLOAT eb[4][CBANDS], FLOAT thr[4][CBANDS],
|
||
|
const FLOAT cb_mld[CBANDS], const FLOAT ath_cb[CBANDS], FLOAT athlower,
|
||
|
FLOAT msfix, int n)
|
||
|
{
|
||
|
FLOAT const msfix2 = msfix * 2.f;
|
||
|
FLOAT rside, rmid;
|
||
|
int b;
|
||
|
for (b = 0; b < n; ++b) {
|
||
|
FLOAT const ebM = eb[2][b];
|
||
|
FLOAT const ebS = eb[3][b];
|
||
|
FLOAT const thmL = thr[0][b];
|
||
|
FLOAT const thmR = thr[1][b];
|
||
|
FLOAT thmM = thr[2][b];
|
||
|
FLOAT thmS = thr[3][b];
|
||
|
|
||
|
/* use this fix if L & R masking differs by 2db or less */
|
||
|
/* if db = 10*log10(x2/x1) < 2 */
|
||
|
/* if (x2 < 1.58*x1) { */
|
||
|
if (thmL <= 1.58f * thmR && thmR <= 1.58f * thmL) {
|
||
|
FLOAT const mld_m = cb_mld[b] * ebS;
|
||
|
FLOAT const mld_s = cb_mld[b] * ebM;
|
||
|
FLOAT const tmp_m = Min(thmS, mld_m);
|
||
|
FLOAT const tmp_s = Min(thmM, mld_s);
|
||
|
rmid = Max(thmM, tmp_m);
|
||
|
rside = Max(thmS, tmp_s);
|
||
|
}
|
||
|
else {
|
||
|
rmid = thmM;
|
||
|
rside = thmS;
|
||
|
}
|
||
|
if (msfix > 0.f) {
|
||
|
/***************************************************************/
|
||
|
/* Adjust M/S maskings if user set "msfix" */
|
||
|
/***************************************************************/
|
||
|
/* Naoki Shibata 2000 */
|
||
|
FLOAT thmLR, thmMS;
|
||
|
FLOAT const ath = ath_cb[b] * athlower;
|
||
|
FLOAT const tmp_l = Max(thmL, ath);
|
||
|
FLOAT const tmp_r = Max(thmR, ath);
|
||
|
thmLR = Min(tmp_l, tmp_r);
|
||
|
thmM = Max(rmid, ath);
|
||
|
thmS = Max(rside, ath);
|
||
|
thmMS = thmM + thmS;
|
||
|
if (thmMS > 0.f && (thmLR * msfix2) < thmMS) {
|
||
|
FLOAT const f = thmLR * msfix2 / thmMS;
|
||
|
thmM *= f;
|
||
|
thmS *= f;
|
||
|
assert(thmMS > 0.f);
|
||
|
}
|
||
|
rmid = Min(thmM, rmid);
|
||
|
rside = Min(thmS, rside);
|
||
|
}
|
||
|
if (rmid > ebM) {
|
||
|
rmid = ebM;
|
||
|
}
|
||
|
if (rside > ebS) {
|
||
|
rside = ebS;
|
||
|
}
|
||
|
thr[2][b] = rmid;
|
||
|
thr[3][b] = rside;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
/*
|
||
|
* NOTE: the bitrate reduction from the inter-channel masking effect is low
|
||
|
* compared to the chance of getting annyoing artefacts. L3psycho_anal_vbr does
|
||
|
* not use this feature. (Robert 071216)
|
||
|
*/
|
||
|
|
||
|
int
|
||
|
L3psycho_anal_vbr(lame_internal_flags * gfc,
|
||
|
const sample_t * const buffer[2], int gr_out,
|
||
|
III_psy_ratio masking_ratio[2][2],
|
||
|
III_psy_ratio masking_MS_ratio[2][2],
|
||
|
FLOAT percep_entropy[2], FLOAT percep_MS_entropy[2],
|
||
|
FLOAT energy[4], int blocktype_d[2])
|
||
|
{
|
||
|
SessionConfig_t const *const cfg = &gfc->cfg;
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_CB2SB_t const *const gdl = &gfc->cd_psy->l;
|
||
|
PsyConst_CB2SB_t const *const gds = &gfc->cd_psy->s;
|
||
|
plotting_data *plt = cfg->analysis ? gfc->pinfo : 0;
|
||
|
|
||
|
III_psy_xmin last_thm[4];
|
||
|
|
||
|
/* fft and energy calculation */
|
||
|
FLOAT(*wsamp_l)[BLKSIZE];
|
||
|
FLOAT(*wsamp_s)[3][BLKSIZE_s];
|
||
|
FLOAT fftenergy[HBLKSIZE];
|
||
|
FLOAT fftenergy_s[3][HBLKSIZE_s];
|
||
|
FLOAT wsamp_L[2][BLKSIZE];
|
||
|
FLOAT wsamp_S[2][3][BLKSIZE_s];
|
||
|
FLOAT eb[4][CBANDS], thr[4][CBANDS];
|
||
|
|
||
|
FLOAT sub_short_factor[4][3];
|
||
|
FLOAT thmm;
|
||
|
FLOAT const pcfact = 0.6f;
|
||
|
FLOAT const ath_factor =
|
||
|
(cfg->msfix > 0.f) ? (cfg->ATH_offset_factor * gfc->ATH->adjust_factor) : 1.f;
|
||
|
|
||
|
const FLOAT(*const_eb)[CBANDS] = (const FLOAT(*)[CBANDS]) eb;
|
||
|
const FLOAT(*const_fftenergy_s)[HBLKSIZE_s] = (const FLOAT(*)[HBLKSIZE_s]) fftenergy_s;
|
||
|
|
||
|
/* block type */
|
||
|
int ns_attacks[4][4] = { {0, 0, 0, 0}, {0, 0, 0, 0}, {0, 0, 0, 0}, {0, 0, 0, 0} };
|
||
|
int uselongblock[2];
|
||
|
|
||
|
/* usual variables like loop indices, etc.. */
|
||
|
int chn, sb, sblock;
|
||
|
|
||
|
/* chn=2 and 3 = Mid and Side channels */
|
||
|
int const n_chn_psy = (cfg->mode == JOINT_STEREO) ? 4 : cfg->channels_out;
|
||
|
|
||
|
memcpy(&last_thm[0], &psv->thm[0], sizeof(last_thm));
|
||
|
|
||
|
vbrpsy_attack_detection(gfc, buffer, gr_out, masking_ratio, masking_MS_ratio, energy,
|
||
|
sub_short_factor, ns_attacks, uselongblock);
|
||
|
|
||
|
vbrpsy_compute_block_type(cfg, uselongblock);
|
||
|
|
||
|
/* LONG BLOCK CASE */
|
||
|
{
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
int const ch01 = chn & 0x01;
|
||
|
|
||
|
wsamp_l = wsamp_L + ch01;
|
||
|
vbrpsy_compute_fft_l(gfc, buffer, chn, gr_out, fftenergy, wsamp_l);
|
||
|
vbrpsy_compute_loudness_approximation_l(gfc, gr_out, chn, fftenergy);
|
||
|
vbrpsy_compute_masking_l(gfc, fftenergy, eb[chn], thr[chn], chn);
|
||
|
}
|
||
|
if (cfg->mode == JOINT_STEREO) {
|
||
|
if ((uselongblock[0] + uselongblock[1]) == 2) {
|
||
|
vbrpsy_compute_MS_thresholds(const_eb, thr, gdl->mld_cb, gfc->ATH->cb_l,
|
||
|
ath_factor, cfg->msfix, gdl->npart);
|
||
|
}
|
||
|
}
|
||
|
/* TODO: apply adaptive ATH masking here ?? */
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
convert_partition2scalefac_l(gfc, eb[chn], thr[chn], chn);
|
||
|
convert_partition2scalefac_l_to_s(gfc, eb[chn], thr[chn], chn);
|
||
|
}
|
||
|
}
|
||
|
/* SHORT BLOCKS CASE */
|
||
|
{
|
||
|
int const force_short_block_calc = gfc->cd_psy->force_short_block_calc;
|
||
|
for (sblock = 0; sblock < 3; sblock++) {
|
||
|
for (chn = 0; chn < n_chn_psy; ++chn) {
|
||
|
int const ch01 = chn & 0x01;
|
||
|
if (uselongblock[ch01] && !force_short_block_calc) {
|
||
|
vbrpsy_skip_masking_s(gfc, chn, sblock);
|
||
|
}
|
||
|
else {
|
||
|
/* compute masking thresholds for short blocks */
|
||
|
wsamp_s = wsamp_S + ch01;
|
||
|
vbrpsy_compute_fft_s(gfc, buffer, chn, sblock, fftenergy_s, wsamp_s);
|
||
|
vbrpsy_compute_masking_s(gfc, const_fftenergy_s, eb[chn], thr[chn], chn,
|
||
|
sblock);
|
||
|
}
|
||
|
}
|
||
|
if (cfg->mode == JOINT_STEREO) {
|
||
|
if ((uselongblock[0] + uselongblock[1]) == 0) {
|
||
|
vbrpsy_compute_MS_thresholds(const_eb, thr, gds->mld_cb, gfc->ATH->cb_s,
|
||
|
ath_factor, cfg->msfix, gds->npart);
|
||
|
}
|
||
|
}
|
||
|
/* TODO: apply adaptive ATH masking here ?? */
|
||
|
for (chn = 0; chn < n_chn_psy; ++chn) {
|
||
|
int const ch01 = chn & 0x01;
|
||
|
if (!uselongblock[ch01] || force_short_block_calc) {
|
||
|
convert_partition2scalefac_s(gfc, eb[chn], thr[chn], chn, sblock);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/**** short block pre-echo control ****/
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
for (sb = 0; sb < SBMAX_s; sb++) {
|
||
|
FLOAT new_thmm[3], prev_thm, t1, t2;
|
||
|
for (sblock = 0; sblock < 3; sblock++) {
|
||
|
thmm = psv->thm[chn].s[sb][sblock];
|
||
|
thmm *= NS_PREECHO_ATT0;
|
||
|
|
||
|
t1 = t2 = thmm;
|
||
|
|
||
|
if (sblock > 0) {
|
||
|
prev_thm = new_thmm[sblock - 1];
|
||
|
}
|
||
|
else {
|
||
|
prev_thm = last_thm[chn].s[sb][2];
|
||
|
}
|
||
|
if (ns_attacks[chn][sblock] >= 2 || ns_attacks[chn][sblock + 1] == 1) {
|
||
|
t1 = NS_INTERP(prev_thm, thmm, NS_PREECHO_ATT1 * pcfact);
|
||
|
}
|
||
|
thmm = Min(t1, thmm);
|
||
|
if (ns_attacks[chn][sblock] == 1) {
|
||
|
t2 = NS_INTERP(prev_thm, thmm, NS_PREECHO_ATT2 * pcfact);
|
||
|
}
|
||
|
else if ((sblock == 0 && psv->last_attacks[chn] == 3)
|
||
|
|| (sblock > 0 && ns_attacks[chn][sblock - 1] == 3)) { /* 2nd preceeding block */
|
||
|
switch (sblock) {
|
||
|
case 0:
|
||
|
prev_thm = last_thm[chn].s[sb][1];
|
||
|
break;
|
||
|
case 1:
|
||
|
prev_thm = last_thm[chn].s[sb][2];
|
||
|
break;
|
||
|
case 2:
|
||
|
prev_thm = new_thmm[0];
|
||
|
break;
|
||
|
}
|
||
|
t2 = NS_INTERP(prev_thm, thmm, NS_PREECHO_ATT2 * pcfact);
|
||
|
}
|
||
|
|
||
|
thmm = Min(t1, thmm);
|
||
|
thmm = Min(t2, thmm);
|
||
|
|
||
|
/* pulse like signal detection for fatboy.wav and so on */
|
||
|
thmm *= sub_short_factor[chn][sblock];
|
||
|
|
||
|
new_thmm[sblock] = thmm;
|
||
|
}
|
||
|
for (sblock = 0; sblock < 3; sblock++) {
|
||
|
psv->thm[chn].s[sb][sblock] = new_thmm[sblock];
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
psv->last_attacks[chn] = ns_attacks[chn][2];
|
||
|
}
|
||
|
|
||
|
|
||
|
/***************************************************************
|
||
|
* determine final block type
|
||
|
***************************************************************/
|
||
|
vbrpsy_apply_block_type(psv, cfg->channels_out, uselongblock, blocktype_d);
|
||
|
|
||
|
/*********************************************************************
|
||
|
* compute the value of PE to return ... no delay and advance
|
||
|
*********************************************************************/
|
||
|
for (chn = 0; chn < n_chn_psy; chn++) {
|
||
|
FLOAT *ppe;
|
||
|
int type;
|
||
|
III_psy_ratio const *mr;
|
||
|
|
||
|
if (chn > 1) {
|
||
|
ppe = percep_MS_entropy - 2;
|
||
|
type = NORM_TYPE;
|
||
|
if (blocktype_d[0] == SHORT_TYPE || blocktype_d[1] == SHORT_TYPE)
|
||
|
type = SHORT_TYPE;
|
||
|
mr = &masking_MS_ratio[gr_out][chn - 2];
|
||
|
}
|
||
|
else {
|
||
|
ppe = percep_entropy;
|
||
|
type = blocktype_d[chn];
|
||
|
mr = &masking_ratio[gr_out][chn];
|
||
|
}
|
||
|
if (type == SHORT_TYPE) {
|
||
|
ppe[chn] = pecalc_s(mr, gfc->sv_qnt.masking_lower);
|
||
|
}
|
||
|
else {
|
||
|
ppe[chn] = pecalc_l(mr, gfc->sv_qnt.masking_lower);
|
||
|
}
|
||
|
|
||
|
if (plt) {
|
||
|
plt->pe[gr_out][chn] = ppe[chn];
|
||
|
}
|
||
|
}
|
||
|
return 0;
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
|
||
|
/*
|
||
|
* The spreading function. Values returned in units of energy
|
||
|
*/
|
||
|
static FLOAT
|
||
|
s3_func(FLOAT bark)
|
||
|
{
|
||
|
FLOAT tempx, x, tempy, temp;
|
||
|
tempx = bark;
|
||
|
if (tempx >= 0)
|
||
|
tempx *= 3;
|
||
|
else
|
||
|
tempx *= 1.5;
|
||
|
|
||
|
if (tempx >= 0.5 && tempx <= 2.5) {
|
||
|
temp = tempx - 0.5;
|
||
|
x = 8.0 * (temp * temp - 2.0 * temp);
|
||
|
}
|
||
|
else
|
||
|
x = 0.0;
|
||
|
tempx += 0.474;
|
||
|
tempy = 15.811389 + 7.5 * tempx - 17.5 * sqrt(1.0 + tempx * tempx);
|
||
|
|
||
|
if (tempy <= -60.0)
|
||
|
return 0.0;
|
||
|
|
||
|
tempx = exp((x + tempy) * LN_TO_LOG10);
|
||
|
|
||
|
/* Normalization. The spreading function should be normalized so that:
|
||
|
+inf
|
||
|
/
|
||
|
| s3 [ bark ] d(bark) = 1
|
||
|
/
|
||
|
-inf
|
||
|
*/
|
||
|
tempx /= .6609193;
|
||
|
return tempx;
|
||
|
}
|
||
|
|
||
|
#if 0
|
||
|
static FLOAT
|
||
|
norm_s3_func(void)
|
||
|
{
|
||
|
double lim_a = 0, lim_b = 0;
|
||
|
double x = 0, l, h;
|
||
|
for (x = 0; s3_func(x) > 1e-20; x -= 1);
|
||
|
l = x;
|
||
|
h = 0;
|
||
|
while (fabs(h - l) > 1e-12) {
|
||
|
x = (h + l) / 2;
|
||
|
if (s3_func(x) > 0) {
|
||
|
h = x;
|
||
|
}
|
||
|
else {
|
||
|
l = x;
|
||
|
}
|
||
|
}
|
||
|
lim_a = l;
|
||
|
for (x = 0; s3_func(x) > 1e-20; x += 1);
|
||
|
l = 0;
|
||
|
h = x;
|
||
|
while (fabs(h - l) > 1e-12) {
|
||
|
x = (h + l) / 2;
|
||
|
if (s3_func(x) > 0) {
|
||
|
l = x;
|
||
|
}
|
||
|
else {
|
||
|
h = x;
|
||
|
}
|
||
|
}
|
||
|
lim_b = h;
|
||
|
{
|
||
|
double sum = 0;
|
||
|
int const m = 1000;
|
||
|
int i;
|
||
|
for (i = 0; i <= m; ++i) {
|
||
|
double x = lim_a + i * (lim_b - lim_a) / m;
|
||
|
double y = s3_func(x);
|
||
|
sum += y;
|
||
|
}
|
||
|
{
|
||
|
double norm = (m + 1) / (sum * (lim_b - lim_a));
|
||
|
/*printf( "norm = %lf\n",norm); */
|
||
|
return norm;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
#endif
|
||
|
|
||
|
static FLOAT
|
||
|
stereo_demask(double f)
|
||
|
{
|
||
|
/* setup stereo demasking thresholds */
|
||
|
/* formula reverse enginerred from plot in paper */
|
||
|
double arg = freq2bark(f);
|
||
|
arg = (Min(arg, 15.5) / 15.5);
|
||
|
|
||
|
return pow(10.0, 1.25 * (1 - cos(PI * arg)) - 2.5);
|
||
|
}
|
||
|
|
||
|
static void
|
||
|
init_numline(PsyConst_CB2SB_t * gd, FLOAT sfreq, int fft_size,
|
||
|
int mdct_size, int sbmax, int const *scalepos)
|
||
|
{
|
||
|
FLOAT b_frq[CBANDS + 1];
|
||
|
FLOAT const mdct_freq_frac = sfreq / (2.0f * mdct_size);
|
||
|
FLOAT const deltafreq = fft_size / (2.0f * mdct_size);
|
||
|
int partition[HBLKSIZE] = { 0 };
|
||
|
int i, j, ni;
|
||
|
int sfb;
|
||
|
sfreq /= fft_size;
|
||
|
j = 0;
|
||
|
ni = 0;
|
||
|
/* compute numlines, the number of spectral lines in each partition band */
|
||
|
/* each partition band should be about DELBARK wide. */
|
||
|
for (i = 0; i < CBANDS; i++) {
|
||
|
FLOAT bark1;
|
||
|
int j2, nl;
|
||
|
bark1 = freq2bark(sfreq * j);
|
||
|
|
||
|
b_frq[i] = sfreq * j;
|
||
|
|
||
|
for (j2 = j; freq2bark(sfreq * j2) - bark1 < DELBARK && j2 <= fft_size / 2; j2++);
|
||
|
|
||
|
nl = j2 - j;
|
||
|
gd->numlines[i] = nl;
|
||
|
gd->rnumlines[i] = (nl > 0) ? (1.0f / nl) : 0;
|
||
|
|
||
|
ni = i + 1;
|
||
|
|
||
|
while (j < j2) {
|
||
|
assert(j < HBLKSIZE);
|
||
|
partition[j++] = i;
|
||
|
}
|
||
|
if (j > fft_size / 2) {
|
||
|
j = fft_size / 2;
|
||
|
++i;
|
||
|
break;
|
||
|
}
|
||
|
}
|
||
|
assert(i < CBANDS);
|
||
|
b_frq[i] = sfreq * j;
|
||
|
|
||
|
gd->n_sb = sbmax;
|
||
|
gd->npart = ni;
|
||
|
|
||
|
{
|
||
|
j = 0;
|
||
|
for (i = 0; i < gd->npart; i++) {
|
||
|
int const nl = gd->numlines[i];
|
||
|
FLOAT const freq = sfreq * (j + nl / 2);
|
||
|
gd->mld_cb[i] = stereo_demask(freq);
|
||
|
j += nl;
|
||
|
}
|
||
|
for (; i < CBANDS; ++i) {
|
||
|
gd->mld_cb[i] = 1;
|
||
|
}
|
||
|
}
|
||
|
for (sfb = 0; sfb < sbmax; sfb++) {
|
||
|
int i1, i2, bo;
|
||
|
int start = scalepos[sfb];
|
||
|
int end = scalepos[sfb + 1];
|
||
|
|
||
|
i1 = floor(.5 + deltafreq * (start - .5));
|
||
|
if (i1 < 0)
|
||
|
i1 = 0;
|
||
|
i2 = floor(.5 + deltafreq * (end - .5));
|
||
|
|
||
|
if (i2 > fft_size / 2)
|
||
|
i2 = fft_size / 2;
|
||
|
|
||
|
bo = partition[i2];
|
||
|
gd->bm[sfb] = (partition[i1] + partition[i2]) / 2;
|
||
|
gd->bo[sfb] = bo;
|
||
|
|
||
|
/* calculate how much of this band belongs to current scalefactor band */
|
||
|
{
|
||
|
FLOAT const f_tmp = mdct_freq_frac * end;
|
||
|
FLOAT bo_w = (f_tmp - b_frq[bo]) / (b_frq[bo + 1] - b_frq[bo]);
|
||
|
if (bo_w < 0) {
|
||
|
bo_w = 0;
|
||
|
}
|
||
|
else {
|
||
|
if (bo_w > 1) {
|
||
|
bo_w = 1;
|
||
|
}
|
||
|
}
|
||
|
gd->bo_weight[sfb] = bo_w;
|
||
|
}
|
||
|
gd->mld[sfb] = stereo_demask(mdct_freq_frac * start);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
static void
|
||
|
compute_bark_values(PsyConst_CB2SB_t const *gd, FLOAT sfreq, int fft_size,
|
||
|
FLOAT * bval, FLOAT * bval_width)
|
||
|
{
|
||
|
/* compute bark values of each critical band */
|
||
|
int k, j = 0, ni = gd->npart;
|
||
|
sfreq /= fft_size;
|
||
|
for (k = 0; k < ni; k++) {
|
||
|
int const w = gd->numlines[k];
|
||
|
FLOAT bark1, bark2;
|
||
|
|
||
|
bark1 = freq2bark(sfreq * (j));
|
||
|
bark2 = freq2bark(sfreq * (j + w - 1));
|
||
|
bval[k] = .5 * (bark1 + bark2);
|
||
|
|
||
|
bark1 = freq2bark(sfreq * (j - .5));
|
||
|
bark2 = freq2bark(sfreq * (j + w - .5));
|
||
|
bval_width[k] = bark2 - bark1;
|
||
|
j += w;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
static int
|
||
|
init_s3_values(FLOAT ** p, int (*s3ind)[2], int npart,
|
||
|
FLOAT const *bval, FLOAT const *bval_width, FLOAT const *norm)
|
||
|
{
|
||
|
FLOAT s3[CBANDS][CBANDS];
|
||
|
/* The s3 array is not linear in the bark scale.
|
||
|
* bval[x] should be used to get the bark value.
|
||
|
*/
|
||
|
int i, j, k;
|
||
|
int numberOfNoneZero = 0;
|
||
|
|
||
|
memset(&s3[0][0], 0, sizeof(s3));
|
||
|
|
||
|
/* s[i][j], the value of the spreading function,
|
||
|
* centered at band j (masker), for band i (maskee)
|
||
|
*
|
||
|
* i.e.: sum over j to spread into signal barkval=i
|
||
|
* NOTE: i and j are used opposite as in the ISO docs
|
||
|
*/
|
||
|
for (i = 0; i < npart; i++) {
|
||
|
for (j = 0; j < npart; j++) {
|
||
|
FLOAT v = s3_func(bval[i] - bval[j]) * bval_width[j];
|
||
|
s3[i][j] = v * norm[i];
|
||
|
}
|
||
|
}
|
||
|
for (i = 0; i < npart; i++) {
|
||
|
for (j = 0; j < npart; j++) {
|
||
|
if (s3[i][j] > 0.0f)
|
||
|
break;
|
||
|
}
|
||
|
s3ind[i][0] = j;
|
||
|
|
||
|
for (j = npart - 1; j > 0; j--) {
|
||
|
if (s3[i][j] > 0.0f)
|
||
|
break;
|
||
|
}
|
||
|
s3ind[i][1] = j;
|
||
|
numberOfNoneZero += (s3ind[i][1] - s3ind[i][0] + 1);
|
||
|
}
|
||
|
*p = lame_calloc(FLOAT, numberOfNoneZero);
|
||
|
if (!*p)
|
||
|
return -1;
|
||
|
|
||
|
k = 0;
|
||
|
for (i = 0; i < npart; i++)
|
||
|
for (j = s3ind[i][0]; j <= s3ind[i][1]; j++)
|
||
|
(*p)[k++] = s3[i][j];
|
||
|
|
||
|
return 0;
|
||
|
}
|
||
|
|
||
|
int
|
||
|
psymodel_init(lame_global_flags const *gfp)
|
||
|
{
|
||
|
lame_internal_flags *const gfc = gfp->internal_flags;
|
||
|
SessionConfig_t *const cfg = &gfc->cfg;
|
||
|
PsyStateVar_t *const psv = &gfc->sv_psy;
|
||
|
PsyConst_t *gd;
|
||
|
int i, j, b, sb, k;
|
||
|
FLOAT bvl_a = 13, bvl_b = 24;
|
||
|
FLOAT snr_l_a = 0, snr_l_b = 0;
|
||
|
FLOAT snr_s_a = -8.25, snr_s_b = -4.5;
|
||
|
|
||
|
FLOAT bval[CBANDS];
|
||
|
FLOAT bval_width[CBANDS];
|
||
|
FLOAT norm[CBANDS];
|
||
|
FLOAT const sfreq = cfg->samplerate_out;
|
||
|
|
||
|
FLOAT xav = 10, xbv = 12;
|
||
|
FLOAT const minval_low = (0.f - cfg->minval);
|
||
|
|
||
|
if (gfc->cd_psy != 0) {
|
||
|
return 0;
|
||
|
}
|
||
|
memset(norm, 0, sizeof(norm));
|
||
|
|
||
|
gd = lame_calloc(PsyConst_t, 1);
|
||
|
gfc->cd_psy = gd;
|
||
|
|
||
|
gd->force_short_block_calc = gfp->experimentalZ;
|
||
|
|
||
|
psv->blocktype_old[0] = psv->blocktype_old[1] = NORM_TYPE; /* the vbr header is long blocks */
|
||
|
|
||
|
for (i = 0; i < 4; ++i) {
|
||
|
for (j = 0; j < CBANDS; ++j) {
|
||
|
psv->nb_l1[i][j] = 1e20;
|
||
|
psv->nb_l2[i][j] = 1e20;
|
||
|
psv->nb_s1[i][j] = psv->nb_s2[i][j] = 1.0;
|
||
|
}
|
||
|
for (sb = 0; sb < SBMAX_l; sb++) {
|
||
|
psv->en[i].l[sb] = 1e20;
|
||
|
psv->thm[i].l[sb] = 1e20;
|
||
|
}
|
||
|
for (j = 0; j < 3; ++j) {
|
||
|
for (sb = 0; sb < SBMAX_s; sb++) {
|
||
|
psv->en[i].s[sb][j] = 1e20;
|
||
|
psv->thm[i].s[sb][j] = 1e20;
|
||
|
}
|
||
|
psv->last_attacks[i] = 0;
|
||
|
}
|
||
|
for (j = 0; j < 9; j++)
|
||
|
psv->last_en_subshort[i][j] = 10.;
|
||
|
}
|
||
|
|
||
|
|
||
|
/* init. for loudness approx. -jd 2001 mar 27 */
|
||
|
psv->loudness_sq_save[0] = psv->loudness_sq_save[1] = 0.0;
|
||
|
|
||
|
|
||
|
|
||
|
/*************************************************************************
|
||
|
* now compute the psychoacoustic model specific constants
|
||
|
************************************************************************/
|
||
|
/* compute numlines, bo, bm, bval, bval_width, mld */
|
||
|
init_numline(&gd->l, sfreq, BLKSIZE, 576, SBMAX_l, gfc->scalefac_band.l);
|
||
|
assert(gd->l.npart < CBANDS);
|
||
|
compute_bark_values(&gd->l, sfreq, BLKSIZE, bval, bval_width);
|
||
|
|
||
|
/* compute the spreading function */
|
||
|
for (i = 0; i < gd->l.npart; i++) {
|
||
|
double snr = snr_l_a;
|
||
|
if (bval[i] >= bvl_a) {
|
||
|
snr = snr_l_b * (bval[i] - bvl_a) / (bvl_b - bvl_a)
|
||
|
+ snr_l_a * (bvl_b - bval[i]) / (bvl_b - bvl_a);
|
||
|
}
|
||
|
norm[i] = pow(10.0, snr / 10.0);
|
||
|
}
|
||
|
i = init_s3_values(&gd->l.s3, gd->l.s3ind, gd->l.npart, bval, bval_width, norm);
|
||
|
if (i)
|
||
|
return i;
|
||
|
|
||
|
/* compute long block specific values, ATH and MINVAL */
|
||
|
j = 0;
|
||
|
for (i = 0; i < gd->l.npart; i++) {
|
||
|
double x;
|
||
|
|
||
|
/* ATH */
|
||
|
x = FLOAT_MAX;
|
||
|
for (k = 0; k < gd->l.numlines[i]; k++, j++) {
|
||
|
FLOAT const freq = sfreq * j / (1000.0 * BLKSIZE);
|
||
|
FLOAT level;
|
||
|
/* freq = Min(.1,freq); *//* ATH below 100 Hz constant, not further climbing */
|
||
|
level = ATHformula(cfg, freq * 1000) - 20; /* scale to FFT units; returned value is in dB */
|
||
|
level = pow(10., 0.1 * level); /* convert from dB -> energy */
|
||
|
level *= gd->l.numlines[i];
|
||
|
if (x > level)
|
||
|
x = level;
|
||
|
}
|
||
|
gfc->ATH->cb_l[i] = x;
|
||
|
|
||
|
/* MINVAL.
|
||
|
For low freq, the strength of the masking is limited by minval
|
||
|
this is an ISO MPEG1 thing, dont know if it is really needed */
|
||
|
/* FIXME: it does work to reduce low-freq problems in S53-Wind-Sax
|
||
|
and lead-voice samples, but introduces some 3 kbps bit bloat too.
|
||
|
TODO: Further refinement of the shape of this hack.
|
||
|
*/
|
||
|
x = 20.0 * (bval[i] / xav - 1.0);
|
||
|
if (x > 6) {
|
||
|
x = 30;
|
||
|
}
|
||
|
if (x < minval_low) {
|
||
|
x = minval_low;
|
||
|
}
|
||
|
if (cfg->samplerate_out < 44000) {
|
||
|
x = 30;
|
||
|
}
|
||
|
x -= 8.;
|
||
|
gd->l.minval[i] = pow(10.0, x / 10.) * gd->l.numlines[i];
|
||
|
}
|
||
|
|
||
|
/************************************************************************
|
||
|
* do the same things for short blocks
|
||
|
************************************************************************/
|
||
|
init_numline(&gd->s, sfreq, BLKSIZE_s, 192, SBMAX_s, gfc->scalefac_band.s);
|
||
|
assert(gd->s.npart < CBANDS);
|
||
|
compute_bark_values(&gd->s, sfreq, BLKSIZE_s, bval, bval_width);
|
||
|
|
||
|
/* SNR formula. short block is normalized by SNR. is it still right ? */
|
||
|
j = 0;
|
||
|
for (i = 0; i < gd->s.npart; i++) {
|
||
|
double x;
|
||
|
double snr = snr_s_a;
|
||
|
if (bval[i] >= bvl_a) {
|
||
|
snr = snr_s_b * (bval[i] - bvl_a) / (bvl_b - bvl_a)
|
||
|
+ snr_s_a * (bvl_b - bval[i]) / (bvl_b - bvl_a);
|
||
|
}
|
||
|
norm[i] = pow(10.0, snr / 10.0);
|
||
|
|
||
|
/* ATH */
|
||
|
x = FLOAT_MAX;
|
||
|
for (k = 0; k < gd->s.numlines[i]; k++, j++) {
|
||
|
FLOAT const freq = sfreq * j / (1000.0 * BLKSIZE_s);
|
||
|
FLOAT level;
|
||
|
/* freq = Min(.1,freq); *//* ATH below 100 Hz constant, not further climbing */
|
||
|
level = ATHformula(cfg, freq * 1000) - 20; /* scale to FFT units; returned value is in dB */
|
||
|
level = pow(10., 0.1 * level); /* convert from dB -> energy */
|
||
|
level *= gd->s.numlines[i];
|
||
|
if (x > level)
|
||
|
x = level;
|
||
|
}
|
||
|
gfc->ATH->cb_s[i] = x;
|
||
|
|
||
|
/* MINVAL.
|
||
|
For low freq, the strength of the masking is limited by minval
|
||
|
this is an ISO MPEG1 thing, dont know if it is really needed */
|
||
|
x = 7.0 * (bval[i] / xbv - 1.0);
|
||
|
if (bval[i] > xbv) {
|
||
|
x *= 1 + log(1 + x) * 3.1;
|
||
|
}
|
||
|
if (bval[i] < xbv) {
|
||
|
x *= 1 + log(1 - x) * 2.3;
|
||
|
}
|
||
|
if (x > 6) {
|
||
|
x = 30;
|
||
|
}
|
||
|
if (x < minval_low) {
|
||
|
x = minval_low;
|
||
|
}
|
||
|
if (cfg->samplerate_out < 44000) {
|
||
|
x = 30;
|
||
|
}
|
||
|
x -= 8;
|
||
|
gd->s.minval[i] = pow(10.0, x / 10) * gd->s.numlines[i];
|
||
|
}
|
||
|
|
||
|
i = init_s3_values(&gd->s.s3, gd->s.s3ind, gd->s.npart, bval, bval_width, norm);
|
||
|
if (i)
|
||
|
return i;
|
||
|
|
||
|
|
||
|
init_mask_add_max_values();
|
||
|
init_fft(gfc);
|
||
|
|
||
|
/* setup temporal masking */
|
||
|
gd->decay = exp(-1.0 * LOG10 / (temporalmask_sustain_sec * sfreq / 192.0));
|
||
|
|
||
|
{
|
||
|
FLOAT msfix;
|
||
|
msfix = NS_MSFIX;
|
||
|
if (cfg->use_safe_joint_stereo)
|
||
|
msfix = 1.0;
|
||
|
if (fabs(cfg->msfix) > 0.0)
|
||
|
msfix = cfg->msfix;
|
||
|
cfg->msfix = msfix;
|
||
|
|
||
|
/* spread only from npart_l bands. Normally, we use the spreading
|
||
|
* function to convolve from npart_l down to npart_l bands
|
||
|
*/
|
||
|
for (b = 0; b < gd->l.npart; b++)
|
||
|
if (gd->l.s3ind[b][1] > gd->l.npart - 1)
|
||
|
gd->l.s3ind[b][1] = gd->l.npart - 1;
|
||
|
}
|
||
|
|
||
|
/* prepare for ATH auto adjustment:
|
||
|
* we want to decrease the ATH by 12 dB per second
|
||
|
*/
|
||
|
#define frame_duration (576. * cfg->mode_gr / sfreq)
|
||
|
gfc->ATH->decay = pow(10., -12. / 10. * frame_duration);
|
||
|
gfc->ATH->adjust_factor = 0.01; /* minimum, for leading low loudness */
|
||
|
gfc->ATH->adjust_limit = 1.0; /* on lead, allow adjust up to maximum */
|
||
|
#undef frame_duration
|
||
|
|
||
|
assert(gd->l.bo[SBMAX_l - 1] <= gd->l.npart);
|
||
|
assert(gd->s.bo[SBMAX_s - 1] <= gd->s.npart);
|
||
|
|
||
|
if (cfg->ATHtype != -1) {
|
||
|
/* compute equal loudness weights (eql_w) */
|
||
|
FLOAT freq;
|
||
|
FLOAT const freq_inc = (FLOAT) cfg->samplerate_out / (FLOAT) (BLKSIZE);
|
||
|
FLOAT eql_balance = 0.0;
|
||
|
freq = 0.0;
|
||
|
for (i = 0; i < BLKSIZE / 2; ++i) {
|
||
|
/* convert ATH dB to relative power (not dB) */
|
||
|
/* to determine eql_w */
|
||
|
freq += freq_inc;
|
||
|
gfc->ATH->eql_w[i] = 1. / pow(10, ATHformula(cfg, freq) / 10);
|
||
|
eql_balance += gfc->ATH->eql_w[i];
|
||
|
}
|
||
|
eql_balance = 1.0 / eql_balance;
|
||
|
for (i = BLKSIZE / 2; --i >= 0;) { /* scale weights */
|
||
|
gfc->ATH->eql_w[i] *= eql_balance;
|
||
|
}
|
||
|
}
|
||
|
{
|
||
|
for (b = j = 0; b < gd->s.npart; ++b) {
|
||
|
for (i = 0; i < gd->s.numlines[b]; ++i) {
|
||
|
++j;
|
||
|
}
|
||
|
}
|
||
|
assert(j == 129);
|
||
|
for (b = j = 0; b < gd->l.npart; ++b) {
|
||
|
for (i = 0; i < gd->l.numlines[b]; ++i) {
|
||
|
++j;
|
||
|
}
|
||
|
}
|
||
|
assert(j == 513);
|
||
|
}
|
||
|
/* short block attack threshold */
|
||
|
{
|
||
|
float x = gfp->attackthre;
|
||
|
float y = gfp->attackthre_s;
|
||
|
if (x < 0) {
|
||
|
x = NSATTACKTHRE;
|
||
|
}
|
||
|
if (y < 0) {
|
||
|
y = NSATTACKTHRE_S;
|
||
|
}
|
||
|
gd->attack_threshold[0] = gd->attack_threshold[1] = gd->attack_threshold[2] = x;
|
||
|
gd->attack_threshold[3] = y;
|
||
|
}
|
||
|
{
|
||
|
float sk_s = -10.f, sk_l = -4.7f;
|
||
|
static float const sk[] =
|
||
|
{ -7.4, -7.4, -7.4, -9.5, -7.4, -6.1, -5.5, -4.7, -4.7, -4.7, -4.7 };
|
||
|
if (gfp->VBR_q < 4) {
|
||
|
sk_l = sk_s = sk[0];
|
||
|
}
|
||
|
else {
|
||
|
sk_l = sk_s = sk[gfp->VBR_q] + gfp->VBR_q_frac * (sk[gfp->VBR_q] - sk[gfp->VBR_q + 1]);
|
||
|
}
|
||
|
b = 0;
|
||
|
for (; b < gd->s.npart; b++) {
|
||
|
float m = (float) (gd->s.npart - b) / gd->s.npart;
|
||
|
gd->s.masking_lower[b] = powf(10.f, sk_s * m * 0.1f);
|
||
|
}
|
||
|
for (; b < CBANDS; ++b) {
|
||
|
gd->s.masking_lower[b] = 1.f;
|
||
|
}
|
||
|
b = 0;
|
||
|
for (; b < gd->l.npart; b++) {
|
||
|
float m = (float) (gd->l.npart - b) / gd->l.npart;
|
||
|
gd->l.masking_lower[b] = powf(10.f, sk_l * m * 0.1f);
|
||
|
}
|
||
|
for (; b < CBANDS; ++b) {
|
||
|
gd->l.masking_lower[b] = 1.f;
|
||
|
}
|
||
|
}
|
||
|
memcpy(&gd->l_to_s, &gd->l, sizeof(gd->l_to_s));
|
||
|
init_numline(&gd->l_to_s, sfreq, BLKSIZE, 192, SBMAX_s, gfc->scalefac_band.s);
|
||
|
return 0;
|
||
|
}
|