[FFmpeg-devel] [RFC] AAC Encoder
Kostya
kostya.shishkov
Sat Aug 16 17:00:39 CEST 2008
On Sat, Aug 16, 2008 at 03:57:56AM +0200, Michael Niedermayer wrote:
> On Fri, Aug 15, 2008 at 07:59:52PM +0300, Kostya wrote:
> [...]
>
> > /**
> > * Set window sequence and related parameters for channel element.
> > *
> > * @param ctx model context
> > * @param audio samples for the current frame
> > * @param la lookahead samples (NULL when unavailable)
> > * @param tag number of channel element to analyze
> > * @param type channel element type (e.g. ID_SCE or ID_CPE)
> > * @param cpe pointer to the current channel element
> > */
> > void ff_aac_psy_suggest_window(AACPsyContext *ctx, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe);
>
> I really think this should return the window size as int
> 0 could mean "dont know try both" possibly, of course it can be done
> differently.
It also set window shape (sine/KBD) and does that for up to two channels.
As for "don't know" window type, it will require some radical changes in
encoder and model and may be considered only as a future thing.
> [...]
> > /**
> > * Quantize one coefficient.
> > * @return absolute value of the quantized coefficient
> > * @see 3GPP TS26.403 5.6.2 "Scalefactor determination"
> > */
> > static av_always_inline int quant(float coef, const float Q)
> > {
> > return av_clip((int)(pow(fabsf(coef) * Q, 0.75) + 0.4054), 0, 8191);
> > }
>
> converting float to int by casting is rather slow on x86
> also i do not see why the cliping against 0 is done
>
> and where does the 0.4054 come from? How has this value been selected?
ask 3GPP folks, in their spec (there's a reference in the comment above)
it's also called MAGIC_NUMBER.
as for clipping, it seemed more logical than applying FFMIN()
> >
> > /**
> > * Convert coefficients to integers.
>
> > * @return sum of coefficients
>
> this is not true, its the sum of their absolute values
corrected
> [...]
> >
> > /**
> > * constants for 3GPP AAC psychoacoustic model
> > * @{
> > */
> > #define PSY_3GPP_C1 3.0f // log2(8.0)
> > #define PSY_3GPP_C2 1.32192809488736234787f // log2(2.5)
> > #define PSY_3GPP_C3 0.55935730170421255071f // 1 - C2/C1
> >
> > #define PSY_3GPP_SPREAD_LOW 1.5f // spreading factor for ascending threshold spreading (15 dB/Bark)
> > #define PSY_3GPP_SPREAD_HI 3.0f // spreading factor for descending threshold spreading (30 dB/Bark)
> >
>
> > #define PSY_3GPP_RPEMIN 0.01f
> > #define PSY_3GPP_RPELEV 2.0f
>
> RPE ?
> please document what that means, iam no psychoacoustic guru
> Its easier to review code when one knows what something is.
Oh, please become one :)
Do you see any comments about them? That's because it's hard to say
anything about them. All I know is that they have some relation to
pre-echo control.
> > /**
> > * @}
> > */
> >
> > /**
> > * information for single band used by 3GPP TS26.403-inspired psychoacoustic model
> > */
> > typedef struct Psy3gppBand{
> > float energy; ///< band energy
> > float ffac; ///< form factor
> > float thr; ///< energy threshold
> > float pe; ///< perceptual entropy
>
> > float a; ///< constant part in perceptual entropy
> > float b; ///< variable part in perceptual entropy
>
> no, single letter variable names are not good for structs
> iam also not truly happy about pe and nl either but they at least have names
> matching the initial letters of what the abbreviate.
taken from the spec, it's also the case when it's hard to give any
sane name to it
> > float nl; ///< predicted number of lines left after quantization
> > float min_snr; ///< minimal SNR
> > float thr_quiet; ///< threshold in quiet
> > }Psy3gppBand;
> >
> > /**
> > * single/pair channel context for psychoacoustic model
> > */
> > typedef struct Psy3gppChannel{
> > float a[2]; ///< parameter used for perceptual entropy - constant part
> > float b[2]; ///< parameter used for perceptual entropy - variable part
> > float pe[2]; ///< channel perceptual entropy
> > float thr[2]; ///< channel thresholds sum
>
> this feels somewhat duplicated from above, iam not saying i want it to
> be changed though, i first need to better understand the code
those are simply sums from all bands for each channel,
they are used in final calculation.
> > Psy3gppBand band[2][128]; ///< bands information
> > Psy3gppBand prev_band[2][128]; ///< bands information from the previous frame
>
> no next_band? yes it may be a naive question but my naive mind would consider
> the next to be usefull as well when the previous is.
previous frame band data is used for pre-echo control,
while next frame band data is nor known yet (but it may
be used in the same way indeed)
> >
> > float win_nrg[2]; ///< sliding average of channel energy
>
> nrg is not an acceptable abbreviation for energy
renamed
> [...]
> > /**
> > * Tell encoder which window types to use.
> > * @see 3GPP TS26.403 5.4.1 "Blockswitching"
> > */
> > static void psy_3gpp_window(AACPsyContext *apc, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe)
> > {
> > int ch;
> > int chans = type == ID_CPE ? 2 : 1;
> > int i, j;
> > int br = apc->avctx->bit_rate / apc->avctx->channels;
> > int attack_ratio = (br <= 16000 + 8000*chans) ? 18 : 10;
> > Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
> > Psy3gppChannel *pch = &pctx->ch[tag];
> > uint8_t grouping[2];
> > enum WindowSequence win[2];
> >
>
> > if(la && !(apc->flags & PSY_MODEL_NO_SWITCH)){
> > float s[8], v;
> > for(ch = 0; ch < chans; ch++){
> > enum WindowSequence last_window_sequence = cpe->ch[ch].ics.window_sequence[0];
> > int switch_to_eight = 0;
> > float sum = 0.0, sum2 = 0.0;
> > int attack_n = 0;
> > for(i = 0; i < 8; i++){
> > for(j = 0; j < 128; j++){
> > v = iir_filter(audio[(i*128+j)*apc->avctx->channels+ch], pch->iir_state[ch]);
>
> this filter can be unrolled by a factor of 2 to avoid some moves in its
> state (like the low pass one)
that's useless. It's order-1 filter after all.
> > sum += v*v;
> > }
> > s[i] = sum;
> > sum2 += sum;
> > }
> > for(i = 0; i < 8; i++){
> > if(s[i] > pch->win_nrg[ch] * attack_ratio){
> > attack_n = i + 1;
> > switch_to_eight = 1;
> > break;
> > }
> > }
> > pch->win_nrg[ch] = pch->win_nrg[ch]*7/8 + sum2/64;
> >
> > switch(last_window_sequence){
> > case ONLY_LONG_SEQUENCE:
> > win[ch] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
> > grouping[ch] = 0;
> > break;
> > case LONG_START_SEQUENCE:
> > win[ch] = EIGHT_SHORT_SEQUENCE;
> > grouping[ch] = pch->next_grouping[ch];
> > break;
> > case LONG_STOP_SEQUENCE:
> > win[ch] = ONLY_LONG_SEQUENCE;
> > grouping[ch] = 0;
> > break;
> > case EIGHT_SHORT_SEQUENCE:
> > win[ch] = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
> > grouping[ch] = switch_to_eight ? pch->next_grouping[ch] : 0;
> > break;
> > }
> > pch->next_grouping[ch] = window_grouping[attack_n];
> > }
>
> How much quality is lost by using this compared to RD optimal switching?
err, is there such thing as quality?
Per my understanding, 8 short windows sequence is used for better preserving
of sudden change of signal. And the change decision is implemented after
the same 3GPP spec.
> [...]
>
> > /**
> > * Modify threshold by adding some value in loudness domain.
> > * @see 3GPP TS26.403 5.6.1.1.1 "Addition of noise with equal loudness"
> > */
> > static inline float modify_thr(float thr, float r){
> > float t;
> > t = pow(thr, 0.25) + r;
> > return t*t*t*t;
>
> (t*t)*(t*t)
> might help the compiler optimize it
ok
> [...]
> > /**
> > * Determine scalefactors and prepare coefficients for encoding.
> > * @see 3GPP TS26.403 5.4 "Psychoacoustic model"
> > */
> > static void psy_3gpp_process(AACPsyContext *apc, int tag, int type, ChannelElement *cpe)
> > {
> > int start;
> > int ch, w, wg, g, g2, i;
> > int prev_scale;
> > Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
> > float pe_target;
> > int bits_avail;
> > int chans = type == ID_CPE ? 2 : 1;
> > Psy3gppChannel *pch = &pctx->ch[tag];
> >
> > //calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
> > memset(pch->band, 0, sizeof(pch->band));
> > for(ch = 0; ch < chans; ch++){
> > start = 0;
> > for(w = 0; w < cpe->ch[ch].ics.num_windows; w++){
> > for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
> > g2 = w*16 + g;
> > for(i = 0; i < cpe->ch[ch].ics.swb_sizes[g]; i++)
> > pch->band[ch][g2].energy += cpe->ch[ch].coeffs[start+i] * cpe->ch[ch].coeffs[start+i];
>
> > pch->band[ch][g2].energy /= 262144.0f;
>
> and this factor does what?
> besides it should be *= 1.0/...
I hope gcc will optimize division by constant.
And it's used for compensate effect of input coefficients
being 512 times larger because of throwing out division
from windowing+MDCT operation. The same thing is done
to form factor calculation.
[...]
> > //determine scalefactors - 5.6.2 "Scalefactor determination"
> > for(ch = 0; ch < chans; ch++){
> > prev_scale = -1;
> > for(w = 0; w < cpe->ch[ch].ics.num_windows; w++){
> > for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
> > g2 = w*16 + g;
>
> > cpe->ch[ch].zeroes[w][g] = pch->band[ch][g2].thr >= pch->band[ch][g2].energy;
>
> how much quality is lost compared to full RD decission ? its just a matter of
> checking how many bits this would need which is likely negligible speed wise.
> (assuming you can unentangle the threshold check into a distortion
> computation)
well, energy < threshold means resulting band will be zero anyway,
and without that check weird values for perceptual entropy start
to appear
> > if(cpe->ch[ch].zeroes[w][g]) continue;
> > //spec gives constant for lg() but we scaled it for log2()
> > cpe->ch[ch].sf_idx[w][g] = (int)(2.66667 * (log2(6.75*pch->band[ch][g2].thr) - log2(pch->band[ch][g2].ffac)));
>
> 2.666... * log2(6.75*pch->band[ch][g2].thr / pch->band[ch][g2].ffac)
>
>
>
> > if(prev_scale != -1)
> > cpe->ch[ch].sf_idx[w][g] = av_clip(cpe->ch[ch].sf_idx[w][g], prev_scale - SCALE_MAX_DIFF, prev_scale + SCALE_MAX_DIFF);
> > prev_scale = cpe->ch[ch].sf_idx[w][g];
> > }
> > }
> > }
> > break;
> > case PSY_MODE_QUALITY:
> > for(ch = 0; ch < chans; ch++){
> > start = 0;
> > for(w = 0; w < cpe->ch[ch].ics.num_windows; w++){
> > for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
> > g2 = w*16 + g;
> > if(pch->band[ch][g2].thr >= pch->band[ch][g2].energy){
> > cpe->ch[ch].sf_idx[w][g] = 0;
> > cpe->ch[ch].zeroes[w][g] = 1;
> > }else{
> > cpe->ch[ch].zeroes[w][g] = 0;
> > cpe->ch[ch].sf_idx[w][g] = (int)(2.66667 * (log2(6.75*pch->band[ch][g2].thr) - log2(pch->band[ch][g2].ffac)));
> > while(cpe->ch[ch].sf_idx[ch][g] > 3){
> > float dist = calc_distortion(cpe->ch[ch].coeffs + start, cpe->ch[ch].ics.swb_sizes[g], SCALE_ONE_POS + cpe->ch[ch].sf_idx[ch][g]);
> > if(dist < pch->band[ch][g2].thr) break;
> > cpe->ch[ch].sf_idx[ch][g] -= 3;
> > }
> > }
>
> looks rather similar to the previous cases
partially - it determines primary scalefactor index from threshold
in the same way, what it does to thresholds before that and index
after that differs.
> > start += cpe->ch[ch].ics.swb_sizes[g];
> > }
> > }
> > }
> > break;
> > }
> >
>
> > //limit scalefactors
>
> why? bitstream limits or is this related to psy?
both
> [...]
> > static const AACPsyModel psy_models[AAC_NB_PSY_MODELS] =
> > {
> > {
> > "Null model",
> > NULL,
> > psy_null_window,
> > psy_null_process,
> > NULL,
> > },
> > {
> > "Null model - short windows",
> > NULL,
> > psy_null8_window,
> > psy_null8_process,
> > NULL,
> > },
> > {
> > "3GPP TS 26.403-inspired model",
> > psy_3gpp_init,
> > psy_3gpp_window,
> > psy_3gpp_process,
> > psy_3gpp_end,
> > },
> > };
>
> Iam tempted to suggest that you drop the 2 null models. I see no real
> sense in them. But if you like to keep them thats perfectly fine with me.
> Adding a 4th model for experimenation would possibly make sense
> Also you could keep the 3gpp exactly as the spec says and implement all my
> suggestions rather in a 4th model that would make comparissions easier and
> would give some protection against mistakes ...
ok, dropped one model by now
> >
> > int av_cold ff_aac_psy_init(AACPsyContext *ctx, AVCodecContext *avctx,
> > enum AACPsyModelType model, int elements, int flags,
> > const uint8_t *bands1024, int num_bands1024,
> > const uint8_t *bands128, int num_bands128)
> > {
> > int i;
> >
>
> > if(model >= AAC_NB_PSY_MODELS || !psy_models[model].window || !psy_models[model].process){
> > av_log(avctx, AV_LOG_ERROR, "Invalid psy model\n");
> > return -1;
> > }
>
> is there really any sense in checking .window and .process of a const static
> array?
no
> >
>
> > #ifndef CONFIG_HARDCODED_TABLES
> > for (i = 0; i < 316; i++)
> > ff_aac_pow2sf_tab[i] = pow(2, (i - 200)/4.);
> > #endif /* CONFIG_HARDCODED_TABLES */
>
> this is likely duplicated
it is not. When table is not hardcoded, it should be initialized.
> [...]
> > void ff_aac_psy_preprocess(AACPsyContext *ctx, int16_t *audio, int16_t *dest, int tag, int type)
> > {
> > int chans = type == ID_CPE ? 2 : 1;
> > const int chstride = ctx->avctx->channels;
> > int i, ch;
> > float t[2];
> >
> > if(chans == 1){
>
> > for(ch = 0; ch < chans; ch++){
> > for(i = 0; i < 1024; i++){
> > dest[i * chstride + ch] = audio[i * chstride + ch];
> > }
> > }
>
> memcpy
no, it copies with gaps
> > }else{
> > for(i = 0; i < 1024; i++){
> > if(ctx->flags & PSY_MODEL_NO_ST_ATT){
> > for(ch = 0; ch < 2; ch++)
> > t[ch] = audio[i * chstride + ch];
> > }else{
> > t[0] = audio[i * chstride + 0] * (0.5 + ctx->stereo_att) + audio[i * chstride + 1] * (0.5 - ctx->stereo_att);
> > t[1] = audio[i * chstride + 0] * (0.5 - ctx->stereo_att) + audio[i * chstride + 1] * (0.5 + ctx->stereo_att);
> > }
> > if(!(ctx->flags & PSY_MODEL_NO_LOWPASS)){
> > LPFilterState *is = (LPFilterState*)ctx->lp_state + tag*2;
>
> > for(ch = 0; ch < 2; ch++)
> > t[ch] = ff_lowpass_filter(&ctx->lp_coeffs, is + ch, t[ch]);
>
> i do not think this is compatible with the filter you posted
it is not by now, I will deal with it when commit my filter stuff,
ignore that for now
> > }
> > for(ch = 0; ch < 2; ch++)
> > dest[i * chstride + ch] = av_clip_int16(t[ch]);
>
> we have optimized code for converting float to int16, please use it
I may have overlooked some stuff for now but that's because it's too
hot here to think properly.
> [...]
> --
> Michael GnuPG fingerprint: 9FF2128B147EF6730BADF133611EC787040B0FAB
>
> It is not what we do, but why we do it that matters.
-------------- next part --------------
/*
* AAC encoder psychoacoustic model
* Copyright (C) 2008 Konstantin Shishkov
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
#ifndef FFMPEG_AACPSY_H
#define FFMPEG_AACPSY_H
#include "avcodec.h"
#include "aac.h"
#include "lowpass.h"
enum AACPsyModelType{
AAC_PSY_TEST, ///< a sample model to exercise encoder
AAC_PSY_3GPP, ///< model following recommendations from 3GPP TS 26.403
AAC_NB_PSY_MODELS ///< total number of psychoacoustic models, since it's not a part of the ABI new models can be added freely
};
enum AACPsyModelMode{
PSY_MODE_CBR, ///< follow bitrate as closely as possible
PSY_MODE_ABR, ///< try to achieve bitrate but actual bitrate may differ significantly
PSY_MODE_QUALITY, ///< try to achieve set quality instead of bitrate
};
#define PSY_MODEL_MODE_MASK 0x0000000F ///< bit fields for storing mode (CBR, ABR, VBR)
#define PSY_MODEL_NO_SWITCH 0x00000020 ///< disable window switching
#define PSY_MODEL_NO_ST_ATT 0x00000040 ///< disable stereo attenuation
#define PSY_MODEL_NO_LOWPASS 0x00000080 ///< disable low-pass filtering
#define PSY_MODEL_NO_PREPROC (PSY_MODEL_NO_ST_ATT | PSY_MODEL_NO_LOWPASS)
#define PSY_MODEL_MODE(a) ((a) & PSY_MODEL_MODE_MASK)
/**
* context used by psychoacoustic model
*/
typedef struct AACPsyContext {
AVCodecContext *avctx; ///< encoder context
int flags; ///< model flags
const uint8_t *bands1024; ///< scalefactor band sizes for long (1024 samples) frame
int num_bands1024; ///< number of scalefactor bands for long frame
const uint8_t *bands128; ///< scalefactor band sizes for short (128 samples) frame
int num_bands128; ///< number of scalefactor bands for short frame
const struct AACPsyModel *model; ///< pointer to the psychoacoustic model implementation
void* model_priv_data; ///< psychoacoustic model implementation private data
float stereo_att; ///< stereo attenuation factor
LPFilterCoeffs lp_coeffs; ///< lowpass filter coefficients
LPFilterState *lp_state; ///< lowpass filter state
}AACPsyContext;
typedef struct AACPsyModel {
const char *name;
int (*init) (AACPsyContext *apc, int elements);
void (*window) (AACPsyContext *apc, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe);
void (*process)(AACPsyContext *apc, int tag, int type, ChannelElement *cpe);
void (*end) (AACPsyContext *apc);
}AACPsyModel;
/**
* Initialize psychoacoustic model.
*
* @param ctx model context
* @param avctx codec context
* @param model model implementation that will be used
* @param elements number of channel elements (single channel or channel pair) to handle by model
* @param flags model flags, may be ignored by model if unsupported
* @param bands1024 scalefactor band lengths for long (1024 samples) frame
* @param num_bands1024 number of scalefactor bands for long frame
* @param bands128 scalefactor band lengths for short (128 samples) frame
* @param num_bands128 number of scalefactor bands for short frame
*
* @return zero if successful, a negative value if not
*/
int ff_aac_psy_init(AACPsyContext *ctx, AVCodecContext *avctx,
enum AACPsyModelType model, int elements, int flags,
const uint8_t *bands1024, int num_bands1024,
const uint8_t *bands128, int num_bands128);
/**
* Preprocess audio frame in order to compress it better.
*
* @param ctx model context
* @param audio samples to preprocess
* @param dest place to put filtered samples
* @param tag number of channel element to analyze
* @param type channel element type (e.g. ID_SCE or ID_CPE)
*/
void ff_aac_psy_preprocess(AACPsyContext *ctx, int16_t *audio, int16_t *dest, int tag, int type);
/**
* Set window sequence and related parameters for channel element.
*
* @param ctx model context
* @param audio samples for the current frame
* @param la lookahead samples (NULL when unavailable)
* @param tag number of channel element to analyze
* @param type channel element type (e.g. ID_SCE or ID_CPE)
* @param cpe pointer to the current channel element
*/
void ff_aac_psy_suggest_window(AACPsyContext *ctx, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe);
/**
* Perform psychoacoustic analysis and output coefficients in integer form
* along with scalefactors, M/S flags, etc.
*
* @param ctx model context
* @param tag number of channel element to analyze
* @param type channel element type (e.g. ID_SCE or ID_CPE)
* @param cpe pointer to the current channel element
*/
void ff_aac_psy_analyze(AACPsyContext *ctx, int tag, int type, ChannelElement *cpe);
/**
* Cleanup model context at the end.
*
* @param ctx model context
*/
void ff_aac_psy_end(AACPsyContext *ctx);
#endif /* FFMPEG_AACPSY_H */
-------------- next part --------------
/*
* AAC encoder psychoacoustic model
* Copyright (C) 2008 Konstantin Shishkov
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file aacpsy.c
* AAC encoder psychoacoustic model
*/
#include "avcodec.h"
#include "aacpsy.h"
#include "aactab.h"
/***********************************
* TODOs:
* General:
* better audio preprocessing (add DC highpass filter?)
* more psy models
*
* 3GPP-based psy model:
* thresholds linearization after their modifications for attaining given bitrate
* try other bitrate controlling mechanism (maybe use ratecontrol.c?)
* control quality for quality-based output
**********************************/
/**
* Quantize one coefficient.
* @return absolute value of the quantized coefficient
* @see 3GPP TS26.403 5.6.2 "Scalefactor determination"
*/
static av_always_inline int quant(float coef, const float Q)
{
return av_clip((int)(pow(fabsf(coef) * Q, 0.75) + 0.4054), 0, 8191);
}
/**
* Convert coefficients to integers.
* @return sum of coefficient absolute values
*/
static inline int quantize_coeffs(float *in, int *out, int size, int scale_idx)
{
int i, sign, sum = 0;
const float Q = ff_aac_pow2sf_tab[200 - scale_idx + SCALE_ONE_POS - SCALE_DIV_512];
for(i = 0; i < size; i++){
sign = in[i] > 0.0;
out[i] = quant(in[i], Q);
sum += out[i];
if(sign) out[i] = -out[i];
}
return sum;
}
static inline float calc_distortion(float *c, int size, int scale_idx)
{
int i;
int q;
float coef, unquant, sum = 0.0f;
const float Q = ff_aac_pow2sf_tab[200 - scale_idx + SCALE_ONE_POS - SCALE_DIV_512];
const float IQ = ff_aac_pow2sf_tab[200 + scale_idx - SCALE_ONE_POS + SCALE_DIV_512];
for(i = 0; i < size; i++){
coef = fabs(c[i]);
q = quant(c[i], Q);
unquant = (q * cbrt(q)) * IQ;
sum += (coef - unquant) * (coef - unquant);
}
return sum;
}
/**
* Produce integer coefficients from scalefactors provided by the model.
*/
static void psy_create_output(AACPsyContext *apc, ChannelElement *cpe, int chans)
{
int i, w, w2, wg, g, ch;
int start, sum, maxsfb, cmaxsfb;
for(ch = 0; ch < chans; ch++){
start = 0;
maxsfb = 0;
cpe->ch[ch].pulse.num_pulse = 0;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
sum = 0;
//apply M/S
if(!ch && cpe->ms_mask[w + g]){
for(i = 0; i < cpe->ch[ch].ics.swb_sizes[g]; i++){
cpe->ch[0].coeffs[start+i] = (cpe->ch[0].coeffs[start+i] + cpe->ch[1].coeffs[start+i]) / 2.0;
cpe->ch[1].coeffs[start+i] = cpe->ch[0].coeffs[start+i] - cpe->ch[1].coeffs[start+i];
}
}
if(!cpe->ch[ch].zeroes[w + g])
sum = quantize_coeffs(cpe->ch[ch].coeffs + start, cpe->ch[ch].icoefs + start, cpe->ch[ch].ics.swb_sizes[g], cpe->ch[ch].sf_idx[w + g]);
else
memset(cpe->ch[ch].icoefs + start, 0, cpe->ch[ch].ics.swb_sizes[g] * sizeof(cpe->ch[0].icoefs[0]));
cpe->ch[ch].zeroes[w + g] = !sum;
start += cpe->ch[ch].ics.swb_sizes[g];
}
for(cmaxsfb = cpe->ch[ch].ics.num_swb; cmaxsfb > 0 && cpe->ch[ch].zeroes[w+cmaxsfb-1]; cmaxsfb--);
maxsfb = FFMAX(maxsfb, cmaxsfb);
}
cpe->ch[ch].ics.max_sfb = maxsfb;
//adjust zero bands for window groups
w = 0;
for(wg = 0; wg < cpe->ch[ch].ics.num_window_groups; wg++){
for(g = 0; g < cpe->ch[ch].ics.max_sfb; g++){
i = 1;
for(w2 = 0; w2 < cpe->ch[ch].ics.group_len[wg]*16; w2 += 16){
if(!cpe->ch[ch].zeroes[w + w2 + g]){
i = 0;
break;
}
}
cpe->ch[ch].zeroes[w + g] = i;
}
w += cpe->ch[ch].ics.group_len[wg] * 16;
}
}
if(chans > 1 && cpe->common_window){
int msc = 0;
cpe->ch[0].ics.max_sfb = FFMAX(cpe->ch[0].ics.max_sfb, cpe->ch[1].ics.max_sfb);
cpe->ch[1].ics.max_sfb = cpe->ch[0].ics.max_sfb;
for(w = 0; w < cpe->ch[0].ics.num_windows*16; w += 16)
for(i = 0; i < cpe->ch[0].ics.max_sfb; i++)
if(cpe->ms_mask[w+i]) msc++;
if(msc == 0 || cpe->ch[0].ics.max_sfb == 0) cpe->ms_mode = 0;
else cpe->ms_mode = msc < cpe->ch[0].ics.max_sfb ? 1 : 2;
}
}
static void psy_test_window(AACPsyContext *apc, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe)
{
int ch, i;
int chans = type == TYPE_CPE ? 2 : 1;
for(ch = 0; ch < chans; ch++){
int prev_seq = cpe->ch[ch].ics.window_sequence[1];
cpe->ch[ch].ics.use_kb_window[1] = cpe->ch[ch].ics.use_kb_window[0];
cpe->ch[ch].ics.window_sequence[1] = cpe->ch[ch].ics.window_sequence[0];
switch(cpe->ch[ch].ics.window_sequence[0]){
case ONLY_LONG_SEQUENCE: if(prev_seq == ONLY_LONG_SEQUENCE)cpe->ch[ch].ics.window_sequence[0] = LONG_START_SEQUENCE; break;
case LONG_START_SEQUENCE: cpe->ch[ch].ics.window_sequence[0] = EIGHT_SHORT_SEQUENCE; break;
case EIGHT_SHORT_SEQUENCE: if(prev_seq == EIGHT_SHORT_SEQUENCE)cpe->ch[ch].ics.window_sequence[0] = LONG_STOP_SEQUENCE; break;
case LONG_STOP_SEQUENCE: cpe->ch[ch].ics.window_sequence[0] = ONLY_LONG_SEQUENCE; break;
}
if(cpe->ch[ch].ics.window_sequence[0] != EIGHT_SHORT_SEQUENCE){
cpe->ch[ch].ics.use_kb_window[0] = 1;
cpe->ch[ch].ics.num_windows = 1;
cpe->ch[ch].ics.swb_sizes = apc->bands1024;
cpe->ch[ch].ics.num_swb = apc->num_bands1024;
cpe->ch[ch].ics.num_window_groups = 1;
cpe->ch[ch].ics.group_len[0] = 1;
}else{
cpe->ch[ch].ics.use_kb_window[0] = 1;
cpe->ch[ch].ics.num_windows = 8;
cpe->ch[ch].ics.swb_sizes = apc->bands128;
cpe->ch[ch].ics.num_swb = apc->num_bands128;
cpe->ch[ch].ics.num_window_groups = 4;
for(i = 0; i < 4; i++)
cpe->ch[ch].ics.group_len[i] = 2;
}
}
cpe->common_window = cpe->ch[0].ics.use_kb_window[0] == cpe->ch[1].ics.use_kb_window[0];
}
static void psy_test_process(AACPsyContext *apc, int tag, int type, ChannelElement *cpe)
{
int start;
int w, ch, g, i;
int chans = type == TYPE_CPE ? 2 : 1;
//detect M/S
if(chans > 1 && cpe->common_window){
start = 0;
for(w = 0; w < cpe->ch[0].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[0].ics.num_swb; g++){
float diff = 0.0f;
for(i = 0; i < cpe->ch[0].ics.swb_sizes[g]; i++)
diff += fabs(cpe->ch[0].coeffs[start+i] - cpe->ch[1].coeffs[start+i]);
cpe->ms_mask[w + g] = diff == 0.0;
}
}
}
for(ch = 0; ch < chans; ch++){
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
cpe->ch[ch].sf_idx[w + g] = SCALE_ONE_POS;
cpe->ch[ch].zeroes[w + g] = 0;
}
}
}
psy_create_output(apc, cpe, chans);
}
/**
* constants for 3GPP AAC psychoacoustic model
* @{
*/
#define PSY_3GPP_C1 3.0f // log2(8.0)
#define PSY_3GPP_C2 1.32192809488736234787f // log2(2.5)
#define PSY_3GPP_C3 0.55935730170421255071f // 1 - C2/C1
#define PSY_3GPP_SPREAD_LOW 1.5f // spreading factor for ascending threshold spreading (15 dB/Bark)
#define PSY_3GPP_SPREAD_HI 3.0f // spreading factor for descending threshold spreading (30 dB/Bark)
#define PSY_3GPP_RPEMIN 0.01f
#define PSY_3GPP_RPELEV 2.0f
/**
* @}
*/
/**
* information for single band used by 3GPP TS26.403-inspired psychoacoustic model
*/
typedef struct Psy3gppBand{
float energy; ///< band energy
float ffac; ///< form factor
float thr; ///< energy threshold
float pe; ///< perceptual entropy
float a; ///< constant part in perceptual entropy
float b; ///< variable part in perceptual entropy
float nl; ///< predicted number of lines left after quantization
float min_snr; ///< minimal SNR
float thr_quiet; ///< threshold in quiet
}Psy3gppBand;
/**
* single/pair channel context for psychoacoustic model
*/
typedef struct Psy3gppChannel{
float a[2]; ///< parameter used for perceptual entropy - constant part
float b[2]; ///< parameter used for perceptual entropy - variable part
float pe[2]; ///< channel perceptual entropy
float thr[2]; ///< channel thresholds sum
Psy3gppBand band[2][128]; ///< bands information
Psy3gppBand prev_band[2][128]; ///< bands information from the previous frame
float win_energy[2]; ///< sliding average of channel energy
float iir_state[2][2]; ///< hi-pass IIR filter state
uint8_t next_grouping[2]; ///< stored grouping scheme for the next frame (in case of 8 short window sequence)
enum WindowSequence next_window_seq[2]; ///< window sequence to be used in the next frame
}Psy3gppChannel;
/**
* 3GPP TS26.403-inspired psychoacoustic model specific data
*/
typedef struct Psy3gppContext{
float barks [1024]; ///< Bark value for each spectral line
float bark_l[64]; ///< Bark value for each spectral band in long frame
float bark_s[16]; ///< Bark value for each spectral band in short frame
float s_low_l[64]; ///< spreading factor for low-to-high threshold spreading in long frame
float s_low_s[16]; ///< spreading factor for low-to-high threshold spreading in short frame
float s_hi_l [64]; ///< spreading factor for high-to-low threshold spreading in long frame
float s_hi_s [16]; ///< spreading factor for high-to-low threshold spreading in short frame
int reservoir; ///< bit reservoir fullness
int avg_bits; ///< average frame size of bits for CBR
float ath_l[64]; ///< absolute threshold of hearing per bands in long frame
float ath_s[16]; ///< absolute threshold of hearing per bands in short frame
Psy3gppChannel *ch;
}Psy3gppContext;
/**
* Calculate Bark value for given line.
*/
static inline float calc_bark(float f)
{
return 13.3f * atanf(0.00076f * f) + 3.5f * atanf((f / 7500.0f) * (f / 7500.0f));
}
#define ATH_ADD 4
/**
* Calculate ATH value for given frequency.
* Borrowed from Lame.
*/
static inline float ath(float f, float add)
{
f /= 1000.0f;
return 3.64 * pow(f, -0.8)
- 6.8 * exp(-0.6 * (f - 3.4) * (f - 3.4))
+ 6.0 * exp(-0.15 * (f - 8.7) * (f - 8.7))
+ (0.6 + 0.04 * add) * 0.001 * f * f * f * f;
}
static av_cold int psy_3gpp_init(AACPsyContext *apc, int elements)
{
Psy3gppContext *pctx;
int i, g, start;
float prev, minscale, minath;
apc->model_priv_data = av_mallocz(sizeof(Psy3gppContext));
pctx = (Psy3gppContext*) apc->model_priv_data;
for(i = 0; i < 1024; i++)
pctx->barks[i] = calc_bark(i * apc->avctx->sample_rate / 2048.0);
i = 0;
prev = 0.0;
for(g = 0; g < apc->num_bands1024; g++){
i += apc->bands1024[g];
pctx->bark_l[g] = (pctx->barks[i - 1] + prev) / 2.0;
prev = pctx->barks[i - 1];
}
for(g = 0; g < apc->num_bands1024 - 1; g++){
pctx->s_low_l[g] = pow(10.0, -(pctx->bark_l[g+1] - pctx->bark_l[g]) * PSY_3GPP_SPREAD_LOW);
pctx->s_hi_l [g] = pow(10.0, -(pctx->bark_l[g+1] - pctx->bark_l[g]) * PSY_3GPP_SPREAD_HI);
}
i = 0;
prev = 0.0;
for(g = 0; g < apc->num_bands128; g++){
i += apc->bands128[g];
pctx->bark_s[g] = (pctx->barks[i - 1] + prev) / 2.0;
prev = pctx->barks[i - 1];
}
for(g = 0; g < apc->num_bands128 - 1; g++){
pctx->s_low_s[g] = pow(10.0, -(pctx->bark_s[g+1] - pctx->bark_s[g]) * PSY_3GPP_SPREAD_LOW);
pctx->s_hi_s [g] = pow(10.0, -(pctx->bark_s[g+1] - pctx->bark_s[g]) * PSY_3GPP_SPREAD_HI);
}
start = 0;
minath = ath(3410, ATH_ADD);
for(g = 0; g < apc->num_bands1024; g++){
minscale = ath(apc->avctx->sample_rate * start / 1024.0, ATH_ADD);
for(i = 1; i < apc->bands1024[g]; i++){
minscale = fminf(minscale, ath(apc->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD));
}
pctx->ath_l[g] = minscale - minath;
start += apc->bands1024[g];
}
start = 0;
for(g = 0; g < apc->num_bands128; g++){
minscale = ath(apc->avctx->sample_rate * start / 1024.0, ATH_ADD);
for(i = 1; i < apc->bands128[g]; i++){
minscale = fminf(minscale, ath(apc->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD));
}
pctx->ath_s[g] = minscale - minath;
start += apc->bands128[g];
}
pctx->avg_bits = apc->avctx->bit_rate * 1024 / apc->avctx->sample_rate;
pctx->ch = av_mallocz(sizeof(Psy3gppChannel) * elements);
return 0;
}
/**
* IIR filter used in block switching decision
*/
static float iir_filter(int in, float state[2])
{
float ret;
ret = 0.7548f * (in - state[0]) + 0.5095f * state[1];
state[0] = in;
state[1] = ret;
return ret;
}
/**
* window grouping information stored as bits (0 - new group, 1 - group continues)
*/
static const uint8_t window_grouping[9] = {
0xB6, 0x6C, 0xD8, 0xB2, 0x66, 0xC6, 0x96, 0x36, 0x36
};
/**
* Tell encoder which window types to use.
* @see 3GPP TS26.403 5.4.1 "Blockswitching"
*/
static void psy_3gpp_window(AACPsyContext *apc, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe)
{
int ch;
int chans = type == TYPE_CPE ? 2 : 1;
int i, j;
int br = apc->avctx->bit_rate / apc->avctx->channels;
int attack_ratio = (br <= 16000 + 8000*chans) ? 18 : 10;
Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
Psy3gppChannel *pch = &pctx->ch[tag];
uint8_t grouping[2];
enum WindowSequence win[2];
if(la && !(apc->flags & PSY_MODEL_NO_SWITCH)){
float s[8], v;
for(ch = 0; ch < chans; ch++){
enum WindowSequence last_window_sequence = cpe->ch[ch].ics.window_sequence[0];
int switch_to_eight = 0;
float sum = 0.0, sum2 = 0.0;
int attack_n = 0;
for(i = 0; i < 8; i++){
for(j = 0; j < 128; j++){
v = iir_filter(audio[(i*128+j)*apc->avctx->channels+ch], pch->iir_state[ch]);
sum += v*v;
}
s[i] = sum;
sum2 += sum;
}
for(i = 0; i < 8; i++){
if(s[i] > pch->win_energy[ch] * attack_ratio){
attack_n = i + 1;
switch_to_eight = 1;
break;
}
}
pch->win_energy[ch] = pch->win_energy[ch]*7/8 + sum2/64;
switch(last_window_sequence){
case ONLY_LONG_SEQUENCE:
win[ch] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
grouping[ch] = 0;
break;
case LONG_START_SEQUENCE:
win[ch] = EIGHT_SHORT_SEQUENCE;
grouping[ch] = pch->next_grouping[ch];
break;
case LONG_STOP_SEQUENCE:
win[ch] = ONLY_LONG_SEQUENCE;
grouping[ch] = 0;
break;
case EIGHT_SHORT_SEQUENCE:
win[ch] = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
grouping[ch] = switch_to_eight ? pch->next_grouping[ch] : 0;
break;
}
pch->next_grouping[ch] = window_grouping[attack_n];
}
}else{
for(ch = 0; ch < chans; ch++){
win[ch] = (cpe->ch[ch].ics.window_sequence[0] == EIGHT_SHORT_SEQUENCE) ? EIGHT_SHORT_SEQUENCE : ONLY_LONG_SEQUENCE;
grouping[ch] = (cpe->ch[ch].ics.window_sequence[0] == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0;
}
}
for(ch = 0; ch < chans; ch++){
cpe->ch[ch].ics.window_sequence[0] = win[ch];
cpe->ch[ch].ics.use_kb_window[0] = 1;
if(win[ch] != EIGHT_SHORT_SEQUENCE){
cpe->ch[ch].ics.num_windows = 1;
cpe->ch[ch].ics.swb_sizes = apc->bands1024;
cpe->ch[ch].ics.num_swb = apc->num_bands1024;
cpe->ch[ch].ics.num_window_groups = 1;
cpe->ch[ch].ics.group_len[0] = 1;
}else{
cpe->ch[ch].ics.num_windows = 8;
cpe->ch[ch].ics.swb_sizes = apc->bands128;
cpe->ch[ch].ics.num_swb = apc->num_bands128;
cpe->ch[ch].ics.num_window_groups = 0;
cpe->ch[ch].ics.group_len[0] = 1;
for(i = 0; i < 8; i++){
if((grouping[ch] >> i) & 1){
cpe->ch[ch].ics.group_len[cpe->ch[ch].ics.num_window_groups - 1]++;
}else{
cpe->ch[ch].ics.num_window_groups++;
cpe->ch[ch].ics.group_len[cpe->ch[ch].ics.num_window_groups - 1] = 1;
}
}
}
}
cpe->common_window = chans > 1 && cpe->ch[0].ics.window_sequence[0] == cpe->ch[1].ics.window_sequence[0] && cpe->ch[0].ics.use_kb_window[0] == cpe->ch[1].ics.use_kb_window[0];
if(cpe->common_window && cpe->ch[0].ics.window_sequence[0] == EIGHT_SHORT_SEQUENCE && grouping[0] != grouping[1])
cpe->common_window = 0;
if(PSY_MODEL_MODE(apc->flags) > PSY_MODE_QUALITY){
av_log(apc->avctx, AV_LOG_ERROR, "Unknown mode %d, defaulting to CBR\n", PSY_MODEL_MODE(apc->flags));
}
}
/**
* Modify threshold by adding some value in loudness domain.
* @see 3GPP TS26.403 5.6.1.1.1 "Addition of noise with equal loudness"
*/
static inline float modify_thr(float thr, float r){
float t;
t = pow(thr, 0.25) + r;
return (t*t)*(t*t);
}
/**
* Calculate perceptual entropy and its corresponding values for one band.
* @see 3GPP TS26.403 5.6.1.3 "Calculation of the reduction value"
*/
static void calc_pe(Psy3gppBand *band, int band_width)
{
if(band->energy <= band->thr){
band->a = 0.0f;
band->b = 0.0f;
band->nl = 0.0f;
return;
}
band->nl = band->ffac / pow(band->energy/band_width, 0.25);
if(band->energy >= band->thr * 8.0){
band->a = band->nl * log2(band->energy);
band->b = band->nl;
}else{
band->a = band->nl * (PSY_3GPP_C2 + PSY_3GPP_C3 * log2(band->energy));
band->b = band->nl * PSY_3GPP_C3;
}
band->pe = band->a - band->b * log2(band->thr);
band->min_snr = 1.0 / (pow(2.0, band->pe / band_width) - 1.5);
if(band->min_snr < 1.26f) band->min_snr = 1.26f;
if(band->min_snr > 316.2277f) band->min_snr = 316.2277f;
}
/**
* Determine scalefactors and prepare coefficients for encoding.
* @see 3GPP TS26.403 5.4 "Psychoacoustic model"
*/
static void psy_3gpp_process(AACPsyContext *apc, int tag, int type, ChannelElement *cpe)
{
int start;
int ch, w, wg, g, i;
int prev_scale;
Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
float pe_target;
int bits_avail;
int chans = type == TYPE_CPE ? 2 : 1;
Psy3gppChannel *pch = &pctx->ch[tag];
//calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
memset(pch->band, 0, sizeof(pch->band));
for(ch = 0; ch < chans; ch++){
start = 0;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
for(i = 0; i < cpe->ch[ch].ics.swb_sizes[g]; i++)
pch->band[ch][w+g].energy += cpe->ch[ch].coeffs[start+i] * cpe->ch[ch].coeffs[start+i];
pch->band[ch][w+g].energy /= 262144.0f;
pch->band[ch][w+g].thr = pch->band[ch][w+g].energy * 0.001258925f;
start += cpe->ch[ch].ics.swb_sizes[g];
if(pch->band[ch][w+g].energy != 0.0){
float ffac = 0.0;
for(i = 0; i < cpe->ch[ch].ics.swb_sizes[g]; i++)
ffac += sqrt(FFABS(cpe->ch[ch].coeffs[start+i]));
pch->band[ch][w+g].ffac = ffac / sqrt(512.0);
}
}
}
}
//modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation"
for(ch = 0; ch < chans; ch++){
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 1; g < cpe->ch[ch].ics.num_swb; g++){
if(cpe->ch[ch].ics.num_swb == apc->num_bands1024)
pch->band[ch][w+g].thr = FFMAX(pch->band[ch][w+g].thr, pch->band[ch][w+g-1].thr * pctx->s_low_l[g-1]);
else
pch->band[ch][w+g].thr = FFMAX(pch->band[ch][w+g].thr, pch->band[ch][w+g-1].thr * pctx->s_low_s[g-1]);
}
for(g = cpe->ch[ch].ics.num_swb - 2; g >= 0; g--){
if(cpe->ch[ch].ics.num_swb == apc->num_bands1024)
pch->band[ch][w+g].thr = FFMAX(pch->band[ch][w+g].thr, pch->band[ch][w+g+1].thr * pctx->s_hi_l[g+1]);
else
pch->band[ch][w+g].thr = FFMAX(pch->band[ch][w+g].thr, pch->band[ch][w+g+1].thr * pctx->s_hi_s[g+1]);
}
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(cpe->ch[ch].ics.num_swb == apc->num_bands1024)
pch->band[ch][w+g].thr_quiet = FFMAX(pch->band[ch][w+g].thr, pctx->ath_l[g]);
else
pch->band[ch][w+g].thr_quiet = FFMAX(pch->band[ch][w+g].thr, pctx->ath_s[g]);
pch->band[ch][w+g].thr_quiet = fmaxf(PSY_3GPP_RPEMIN*pch->band[ch][w+g].thr_quiet, fminf(pch->band[ch][w+g].thr_quiet, PSY_3GPP_RPELEV*pch->prev_band[ch][w+g].thr_quiet));
pch->band[ch][w+g].thr = FFMAX(pch->band[ch][w+g].thr, pch->band[ch][w+g].thr_quiet * 0.25);
}
}
}
// M/S detection - 5.5.2 "Mid/Side Stereo"
if(chans > 1 && cpe->common_window){
start = 0;
for(w = 0; w < cpe->ch[0].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[0].ics.num_swb; g++){
double en_m = 0.0, en_s = 0.0, ff_m = 0.0, ff_s = 0.0, minthr;
float m, s;
cpe->ms_mask[w+g] = 0;
if(pch->band[0][w+g].energy == 0.0 || pch->band[1][w+g].energy == 0.0)
continue;
for(i = 0; i < cpe->ch[0].ics.swb_sizes[g]; i++){
m = cpe->ch[0].coeffs[start+i] + cpe->ch[1].coeffs[start+i];
s = cpe->ch[0].coeffs[start+i] - cpe->ch[1].coeffs[start+i];
en_m += m*m;
en_s += s*s;
}
en_m /= 262144.0*4.0;
en_s /= 262144.0*4.0;
minthr = FFMIN(pch->band[0][w+g].thr, pch->band[1][w+g].thr);
if(minthr * minthr * pch->band[0][w+g].energy * pch->band[1][w+g].energy >= (pch->band[0][w+g].thr * pch->band[1][w+g].thr * en_m * en_s)){
cpe->ms_mask[w+g] = 1;
pch->band[0][w+g].energy = en_m;
pch->band[1][w+g].energy = en_s;
pch->band[0][w+g].thr = en_m * 0.001258925f;
pch->band[1][w+g].thr = en_s * 0.001258925f;
for(i = 0; i < cpe->ch[0].ics.swb_sizes[g]; i++){
m = cpe->ch[0].coeffs[start+i] + cpe->ch[1].coeffs[start+i];
s = cpe->ch[0].coeffs[start+i] - cpe->ch[1].coeffs[start+i];
ff_m += sqrt(fabs(m));
ff_s += sqrt(fabs(s));
}
pch->band[0][w+g].ffac = ff_m / 32.0;
pch->band[1][w+g].ffac = ff_s / 32.0;
}
}
}
}
for(ch = 0; ch < chans; ch++){
pch->a[ch] = pch->b[ch] = pch->pe[ch] = pch->thr[ch] = 0.0f;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(pch->band[ch][w+g].energy != 0.0)
calc_pe(&pch->band[ch][w+g], cpe->ch[ch].ics.swb_sizes[g]);
if(pch->band[ch][w+g].thr < pch->band[ch][w+g].energy){
pch->a[ch] += pch->band[ch][w+g].a;
pch->b[ch] += pch->band[ch][w+g].b;
pch->pe[ch] += pch->band[ch][w+g].pe;
pch->thr[ch] += pch->band[ch][w+g].thr;
}
}
}
}
switch(PSY_MODEL_MODE(apc->flags)){
case PSY_MODE_CBR:
case PSY_MODE_ABR:
//bitrate reduction - 5.6.1 "Reduction of psychoacoustic requirements"
if(PSY_MODEL_MODE(apc->flags) != PSY_MODE_ABR){
pctx->reservoir += pctx->avg_bits - apc->avctx->frame_bits;
bits_avail = pctx->avg_bits + pctx->reservoir;
bits_avail = FFMIN(bits_avail, pctx->avg_bits * 1.5);
pe_target = 1.18f * bits_avail / apc->avctx->channels * chans;
}else{
pe_target = pctx->avg_bits / apc->avctx->channels * chans;
}
for(i = 0; i < 2; i++){
float t0, pe, r, a0 = 0.0f, pe0 = 0.0f, b0 = 0.0f;
for(ch = 0; ch < chans; ch++){
a0 += pch->a[ch];
b0 += pch->b[ch];
pe0 += pch->pe[ch];
}
if(pe0 == 0.0f) break;
t0 = pow(2.0, (a0 - pe0) / (4.0 * b0));
r = pow(2.0, (a0 - pe_target) / (4.0 * b0)) - t0;
//add correction factor to thresholds and recalculate perceptual entropy
for(ch = 0; ch < chans; ch++){
pch->a[ch] = pch->b[ch] = pch->pe[ch] = pch->thr[ch] = 0.0;
pe = 0.0f;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
pch->band[ch][w+g].thr = modify_thr(pch->band[ch][w+g].thr, r);
calc_pe(&pch->band[ch][w+g], cpe->ch[ch].ics.swb_sizes[g]);
if(pch->band[ch][w+g].thr < pch->band[ch][w+g].energy){
pch->a[ch] += pch->band[ch][w+g].a;
pch->b[ch] += pch->band[ch][w+g].b;
pch->pe[ch] += pch->band[ch][w+g].pe;
pch->thr[ch] += pch->band[ch][w+g].thr;
}
}
}
}
}
//determine scalefactors - 5.6.2 "Scalefactor determination"
for(ch = 0; ch < chans; ch++){
prev_scale = -1;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
cpe->ch[ch].zeroes[w+g] = pch->band[ch][w+g].thr >= pch->band[ch][w+g].energy;
if(cpe->ch[ch].zeroes[w+g]) continue;
//spec gives constant for lg() but we scaled it for log2()
cpe->ch[ch].sf_idx[w+g] = (int)(2.66667 * (log2(6.75*pch->band[ch][w+g].thr) - log2(pch->band[ch][w+g].ffac)));
if(prev_scale != -1)
cpe->ch[ch].sf_idx[w+g] = av_clip(cpe->ch[ch].sf_idx[w+g], prev_scale - SCALE_MAX_DIFF, prev_scale + SCALE_MAX_DIFF);
prev_scale = cpe->ch[ch].sf_idx[w+g];
}
}
}
break;
case PSY_MODE_QUALITY:
for(ch = 0; ch < chans; ch++){
start = 0;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16){
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(pch->band[ch][w+g].thr >= pch->band[ch][w+g].energy){
cpe->ch[ch].sf_idx[w+g] = 0;
cpe->ch[ch].zeroes[w+g] = 1;
}else{
cpe->ch[ch].zeroes[w+g] = 0;
cpe->ch[ch].sf_idx[w+g] = (int)(2.66667 * (log2(6.75*pch->band[ch][w+g].thr) - log2(pch->band[ch][w+g].ffac)));
while(cpe->ch[ch].sf_idx[w+g] > 3){
float dist = calc_distortion(cpe->ch[ch].coeffs + start, cpe->ch[ch].ics.swb_sizes[g], SCALE_ONE_POS + cpe->ch[ch].sf_idx[w+g]);
if(dist < pch->band[ch][w+g].thr) break;
cpe->ch[ch].sf_idx[w+g] -= 3;
}
}
start += cpe->ch[ch].ics.swb_sizes[g];
}
}
}
break;
}
//limit scalefactors
for(ch = 0; ch < chans; ch++){
int min_scale = 256;
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16)
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(cpe->ch[ch].zeroes[w + g]) continue;
min_scale = FFMIN(min_scale, cpe->ch[ch].sf_idx[w + g]);
}
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16)
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(cpe->ch[ch].zeroes[w + g]) continue;
cpe->ch[ch].sf_idx[w + g] = FFMIN(cpe->ch[ch].sf_idx[w + g], min_scale + SCALE_MAX_DIFF);
}
for(w = 0; w < cpe->ch[ch].ics.num_windows*16; w += 16)
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
if(cpe->ch[ch].zeroes[w + g])
cpe->ch[ch].sf_idx[w + g] = 256;
else
cpe->ch[ch].sf_idx[w + g] = av_clip(SCALE_ONE_POS + cpe->ch[ch].sf_idx[w + g], 0, SCALE_MAX_POS);
}
//adjust scalefactors for window groups
w = 0;
for(wg = 0; wg < cpe->ch[ch].ics.num_window_groups; wg++){
int min_scale = 256;
for(g = 0; g < cpe->ch[ch].ics.num_swb; g++){
for(i = w; i < w + cpe->ch[ch].ics.group_len[wg]*16; i += 16){
if(cpe->ch[ch].zeroes[i + g]) continue;
min_scale = FFMIN(min_scale, cpe->ch[ch].sf_idx[i + g]);
}
for(i = w; i < w + cpe->ch[ch].ics.group_len[wg]*16; i += 16)
cpe->ch[ch].sf_idx[i + g] = min_scale;
}
w += cpe->ch[ch].ics.group_len[wg] * 16;
}
}
memcpy(pch->prev_band, pch->band, sizeof(pch->band));
psy_create_output(apc, cpe, chans);
}
static av_cold void psy_3gpp_end(AACPsyContext *apc)
{
Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
av_freep(&pctx->ch);
av_freep(&apc->model_priv_data);
}
static const AACPsyModel psy_models[AAC_NB_PSY_MODELS] =
{
{
"Test model",
NULL,
psy_test_window,
psy_test_process,
NULL,
},
{
"3GPP TS 26.403-inspired model",
psy_3gpp_init,
psy_3gpp_window,
psy_3gpp_process,
psy_3gpp_end,
},
};
int av_cold ff_aac_psy_init(AACPsyContext *ctx, AVCodecContext *avctx,
enum AACPsyModelType model, int elements, int flags,
const uint8_t *bands1024, int num_bands1024,
const uint8_t *bands128, int num_bands128)
{
int i;
if(model < 0 || model >= AAC_NB_PSY_MODELS){
av_log(avctx, AV_LOG_ERROR, "Invalid psy model\n");
return -1;
}
#ifndef CONFIG_HARDCODED_TABLES
for (i = 0; i < 316; i++)
ff_aac_pow2sf_tab[i] = pow(2, (i - 200)/4.);
#endif /* CONFIG_HARDCODED_TABLES */
ctx->avctx = avctx;
ctx->flags = flags;
ctx->bands1024 = bands1024;
ctx->num_bands1024 = num_bands1024;
ctx->bands128 = bands128;
ctx->num_bands128 = num_bands128;
ctx->model = &psy_models[model];
if(ctx->flags & PSY_MODEL_NO_ST_ATT || PSY_MODEL_MODE(ctx->flags) == PSY_MODE_QUALITY){
ctx->flags |= PSY_MODEL_NO_ST_ATT;
ctx->stereo_att = 0.5f;
}else{
ctx->stereo_att = av_clipf(avctx->bit_rate / elements / 192000.0, 0.0f, 0.5f);
}
if(ctx->flags & PSY_MODEL_NO_LOWPASS || PSY_MODEL_MODE(ctx->flags) == PSY_MODE_QUALITY){
ctx->flags |= PSY_MODEL_NO_LOWPASS;
}else{
int cutoff;
cutoff = avctx->bit_rate / elements / 8;
if(ff_lowpass_filter_init_coeffs(&ctx->lp_coeffs, avctx->sample_rate/2, cutoff) < 0){
ctx->flags |= PSY_MODEL_NO_LOWPASS;
}else{
ctx->lp_state = av_mallocz(sizeof(LPFilterState) * elements * 2);
}
}
if(ctx->model->init)
return ctx->model->init(ctx, elements);
return 0;
}
void ff_aac_psy_suggest_window(AACPsyContext *ctx, int16_t *audio, int16_t *la, int tag, int type, ChannelElement *cpe)
{
ctx->model->window(ctx, audio, la, tag, type, cpe);
}
void ff_aac_psy_analyze(AACPsyContext *ctx, int tag, int type, ChannelElement *cpe)
{
ctx->model->process(ctx, tag, type, cpe);
}
void av_cold ff_aac_psy_end(AACPsyContext *ctx)
{
av_freep(&ctx->lp_state);
if(ctx->model->end)
return ctx->model->end(ctx);
}
void ff_aac_psy_preprocess(AACPsyContext *ctx, int16_t *audio, int16_t *dest, int tag, int type)
{
int chans = type == TYPE_CPE ? 2 : 1;
const int chstride = ctx->avctx->channels;
int i, ch;
float t[2];
if(chans == 1){
for(ch = 0; ch < chans; ch++){
for(i = 0; i < 1024; i++){
dest[i * chstride + ch] = audio[i * chstride + ch];
}
}
}else{
for(i = 0; i < 1024; i++){
if(ctx->flags & PSY_MODEL_NO_ST_ATT){
for(ch = 0; ch < 2; ch++)
t[ch] = audio[i * chstride + ch];
}else{
t[0] = audio[i * chstride + 0] * (0.5 + ctx->stereo_att) + audio[i * chstride + 1] * (0.5 - ctx->stereo_att);
t[1] = audio[i * chstride + 0] * (0.5 - ctx->stereo_att) + audio[i * chstride + 1] * (0.5 + ctx->stereo_att);
}
if(!(ctx->flags & PSY_MODEL_NO_LOWPASS)){
LPFilterState *is = (LPFilterState*)ctx->lp_state + tag*2;
for(ch = 0; ch < 2; ch++)
t[ch] = ff_lowpass_filter(&ctx->lp_coeffs, is + ch, t[ch]);
}
for(ch = 0; ch < 2; ch++)
dest[i * chstride + ch] = av_clip_int16(t[ch]);
}
}
}
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