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ffmpeg/libavcodec/aacpsy.c

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/*
* 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
* AAC encoder psychoacoustic model
*/
#include "avcodec.h"
#include "aactab.h"
#include "psymodel.h"
/***********************************
* TODOs:
* thresholds linearization after their modifications for attaining given bitrate
* try other bitrate controlling mechanism (maybe use ratecontrol.c?)
* control quality for quality-based output
**********************************/
/**
* constants for 3GPP AAC psychoacoustic model
* @{
*/
#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 min_snr; ///< minimal SNR
float thr_quiet; ///< threshold in quiet
}Psy3gppBand;
/**
* single/pair channel context for psychoacoustic model
*/
typedef struct Psy3gppChannel{
Psy3gppBand band[128]; ///< bands information
Psy3gppBand prev_band[128]; ///< bands information from the previous frame
float win_energy; ///< sliding average of channel energy
float iir_state[2]; ///< hi-pass IIR filter state
uint8_t next_grouping; ///< stored grouping scheme for the next frame (in case of 8 short window sequence)
enum WindowSequence next_window_seq; ///< window sequence to be used in the next frame
}Psy3gppChannel;
/**
* psychoacoustic model frame type-dependent coefficients
*/
typedef struct Psy3gppCoeffs{
float ath [64]; ///< absolute threshold of hearing per bands
float barks [64]; ///< Bark value for each spectral band in long frame
float spread_low[64]; ///< spreading factor for low-to-high threshold spreading in long frame
float spread_hi [64]; ///< spreading factor for high-to-low threshold spreading in long frame
}Psy3gppCoeffs;
/**
* 3GPP TS26.403-inspired psychoacoustic model specific data
*/
typedef struct Psy3gppContext{
Psy3gppCoeffs psy_coef[2];
Psy3gppChannel *ch;
}Psy3gppContext;
/**
* Calculate Bark value for given line.
*/
static av_cold 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 av_cold 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(FFPsyContext *ctx) {
Psy3gppContext *pctx;
float barks[1024];
int i, j, g, start;
float prev, minscale, minath;
ctx->model_priv_data = av_mallocz(sizeof(Psy3gppContext));
pctx = (Psy3gppContext*) ctx->model_priv_data;
for (i = 0; i < 1024; i++)
barks[i] = calc_bark(i * ctx->avctx->sample_rate / 2048.0);
minath = ath(3410, ATH_ADD);
for (j = 0; j < 2; j++) {
Psy3gppCoeffs *coeffs = &pctx->psy_coef[j];
i = 0;
prev = 0.0;
for (g = 0; g < ctx->num_bands[j]; g++) {
i += ctx->bands[j][g];
coeffs->barks[g] = (barks[i - 1] + prev) / 2.0;
prev = barks[i - 1];
}
for (g = 0; g < ctx->num_bands[j] - 1; g++) {
coeffs->spread_low[g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_LOW);
coeffs->spread_hi [g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_HI);
}
start = 0;
for (g = 0; g < ctx->num_bands[j]; g++) {
minscale = ath(ctx->avctx->sample_rate * start / 1024.0, ATH_ADD);
for (i = 1; i < ctx->bands[j][g]; i++)
minscale = FFMIN(minscale, ath(ctx->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD));
coeffs->ath[g] = minscale - minath;
start += ctx->bands[j][g];
}
}
pctx->ch = av_mallocz(sizeof(Psy3gppChannel) * ctx->avctx->channels);
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 FFPsyWindowInfo psy_3gpp_window(FFPsyContext *ctx,
const int16_t *audio, const int16_t *la,
int channel, int prev_type)
{
int i, j;
int br = ctx->avctx->bit_rate / ctx->avctx->channels;
int attack_ratio = br <= 16000 ? 18 : 10;
Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
Psy3gppChannel *pch = &pctx->ch[channel];
uint8_t grouping = 0;
FFPsyWindowInfo wi;
memset(&wi, 0, sizeof(wi));
if (la) {
float s[8], v;
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(la[(i*128+j)*ctx->avctx->channels], pch->iir_state);
sum += v*v;
}
s[i] = sum;
sum2 += sum;
}
for (i = 0; i < 8; i++) {
if (s[i] > pch->win_energy * attack_ratio) {
attack_n = i + 1;
switch_to_eight = 1;
break;
}
}
pch->win_energy = pch->win_energy*7/8 + sum2/64;
wi.window_type[1] = prev_type;
switch (prev_type) {
case ONLY_LONG_SEQUENCE:
wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
break;
case LONG_START_SEQUENCE:
wi.window_type[0] = EIGHT_SHORT_SEQUENCE;
grouping = pch->next_grouping;
break;
case LONG_STOP_SEQUENCE:
wi.window_type[0] = ONLY_LONG_SEQUENCE;
break;
case EIGHT_SHORT_SEQUENCE:
wi.window_type[0] = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
grouping = switch_to_eight ? pch->next_grouping : 0;
break;
}
pch->next_grouping = window_grouping[attack_n];
} else {
for (i = 0; i < 3; i++)
wi.window_type[i] = prev_type;
grouping = (prev_type == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0;
}
wi.window_shape = 1;
if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) {
wi.num_windows = 1;
wi.grouping[0] = 1;
} else {
int lastgrp = 0;
wi.num_windows = 8;
for (i = 0; i < 8; i++) {
if (!((grouping >> i) & 1))
lastgrp = i;
wi.grouping[lastgrp]++;
}
}
return wi;
}
/**
* Calculate band thresholds as suggested in 3GPP TS26.403
*/
static void psy_3gpp_analyze(FFPsyContext *ctx, int channel,
const float *coefs, FFPsyWindowInfo *wi)
{
Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
Psy3gppChannel *pch = &pctx->ch[channel];
int start = 0;
int i, w, g;
const int num_bands = ctx->num_bands[wi->num_windows == 8];
const uint8_t* band_sizes = ctx->bands[wi->num_windows == 8];
Psy3gppCoeffs *coeffs = &pctx->psy_coef[wi->num_windows == 8];
//calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
for (w = 0; w < wi->num_windows*16; w += 16) {
for (g = 0; g < num_bands; g++) {
Psy3gppBand *band = &pch->band[w+g];
band->energy = 0.0f;
for (i = 0; i < band_sizes[g]; i++)
band->energy += coefs[start+i] * coefs[start+i];
band->energy *= 1.0f / (512*512);
band->thr = band->energy * 0.001258925f;
start += band_sizes[g];
ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].energy = band->energy;
}
}
//modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation"
for (w = 0; w < wi->num_windows*16; w += 16) {
Psy3gppBand *band = &pch->band[w];
for (g = 1; g < num_bands; g++)
band[g].thr = FFMAX(band[g].thr, band[g-1].thr * coeffs->spread_low[g-1]);
for (g = num_bands - 2; g >= 0; g--)
band[g].thr = FFMAX(band[g].thr, band[g+1].thr * coeffs->spread_hi [g]);
for (g = 0; g < num_bands; g++) {
band[g].thr_quiet = FFMAX(band[g].thr, coeffs->ath[g]);
if (wi->num_windows != 8 && wi->window_type[1] != EIGHT_SHORT_SEQUENCE)
band[g].thr_quiet = FFMAX(PSY_3GPP_RPEMIN*band[g].thr_quiet,
FFMIN(band[g].thr_quiet,
PSY_3GPP_RPELEV*pch->prev_band[w+g].thr_quiet));
band[g].thr = FFMAX(band[g].thr, band[g].thr_quiet * 0.25);
ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].threshold = band[g].thr;
}
}
memcpy(pch->prev_band, pch->band, sizeof(pch->band));
}
static av_cold void psy_3gpp_end(FFPsyContext *apc)
{
Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
av_freep(&pctx->ch);
av_freep(&apc->model_priv_data);
}
const FFPsyModel ff_aac_psy_model =
{
.name = "3GPP TS 26.403-inspired model",
.init = psy_3gpp_init,
.window = psy_3gpp_window,
.analyze = psy_3gpp_analyze,
.end = psy_3gpp_end,
};
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