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31184aac87
Set band info before determining scalefactors. Use the look ahead for windowing decision. Originally committed as revision 23132 to svn://svn.ffmpeg.org/ffmpeg/trunk
319 lines
11 KiB
C
319 lines
11 KiB
C
/*
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* AAC encoder psychoacoustic model
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* Copyright (C) 2008 Konstantin Shishkov
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*
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* This file is part of FFmpeg.
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*
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* FFmpeg is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* FFmpeg 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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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with FFmpeg; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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/**
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* @file
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* AAC encoder psychoacoustic model
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*/
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#include "avcodec.h"
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#include "aactab.h"
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#include "psymodel.h"
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/***********************************
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* TODOs:
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* thresholds linearization after their modifications for attaining given bitrate
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* try other bitrate controlling mechanism (maybe use ratecontrol.c?)
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* control quality for quality-based output
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**********************************/
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/**
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* constants for 3GPP AAC psychoacoustic model
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* @{
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*/
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#define PSY_3GPP_SPREAD_LOW 1.5f // spreading factor for ascending threshold spreading (15 dB/Bark)
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#define PSY_3GPP_SPREAD_HI 3.0f // spreading factor for descending threshold spreading (30 dB/Bark)
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#define PSY_3GPP_RPEMIN 0.01f
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#define PSY_3GPP_RPELEV 2.0f
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/**
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* @}
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*/
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/**
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* information for single band used by 3GPP TS26.403-inspired psychoacoustic model
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*/
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typedef struct Psy3gppBand{
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float energy; ///< band energy
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float ffac; ///< form factor
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float thr; ///< energy threshold
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float min_snr; ///< minimal SNR
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float thr_quiet; ///< threshold in quiet
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}Psy3gppBand;
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/**
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* single/pair channel context for psychoacoustic model
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*/
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typedef struct Psy3gppChannel{
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Psy3gppBand band[128]; ///< bands information
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Psy3gppBand prev_band[128]; ///< bands information from the previous frame
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float win_energy; ///< sliding average of channel energy
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float iir_state[2]; ///< hi-pass IIR filter state
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uint8_t next_grouping; ///< stored grouping scheme for the next frame (in case of 8 short window sequence)
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enum WindowSequence next_window_seq; ///< window sequence to be used in the next frame
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}Psy3gppChannel;
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/**
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* psychoacoustic model frame type-dependent coefficients
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*/
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typedef struct Psy3gppCoeffs{
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float ath [64]; ///< absolute threshold of hearing per bands
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float barks [64]; ///< Bark value for each spectral band in long frame
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float spread_low[64]; ///< spreading factor for low-to-high threshold spreading in long frame
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float spread_hi [64]; ///< spreading factor for high-to-low threshold spreading in long frame
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}Psy3gppCoeffs;
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/**
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* 3GPP TS26.403-inspired psychoacoustic model specific data
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*/
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typedef struct Psy3gppContext{
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Psy3gppCoeffs psy_coef[2];
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Psy3gppChannel *ch;
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}Psy3gppContext;
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/**
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* Calculate Bark value for given line.
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*/
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static av_cold float calc_bark(float f)
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{
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return 13.3f * atanf(0.00076f * f) + 3.5f * atanf((f / 7500.0f) * (f / 7500.0f));
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}
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#define ATH_ADD 4
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/**
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* Calculate ATH value for given frequency.
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* Borrowed from Lame.
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*/
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static av_cold float ath(float f, float add)
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{
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f /= 1000.0f;
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return 3.64 * pow(f, -0.8)
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- 6.8 * exp(-0.6 * (f - 3.4) * (f - 3.4))
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+ 6.0 * exp(-0.15 * (f - 8.7) * (f - 8.7))
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+ (0.6 + 0.04 * add) * 0.001 * f * f * f * f;
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}
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static av_cold int psy_3gpp_init(FFPsyContext *ctx) {
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Psy3gppContext *pctx;
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float barks[1024];
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int i, j, g, start;
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float prev, minscale, minath;
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ctx->model_priv_data = av_mallocz(sizeof(Psy3gppContext));
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pctx = (Psy3gppContext*) ctx->model_priv_data;
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for (i = 0; i < 1024; i++)
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barks[i] = calc_bark(i * ctx->avctx->sample_rate / 2048.0);
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minath = ath(3410, ATH_ADD);
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for (j = 0; j < 2; j++) {
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Psy3gppCoeffs *coeffs = &pctx->psy_coef[j];
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i = 0;
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prev = 0.0;
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for (g = 0; g < ctx->num_bands[j]; g++) {
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i += ctx->bands[j][g];
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coeffs->barks[g] = (barks[i - 1] + prev) / 2.0;
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prev = barks[i - 1];
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}
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for (g = 0; g < ctx->num_bands[j] - 1; g++) {
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coeffs->spread_low[g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_LOW);
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coeffs->spread_hi [g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_HI);
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}
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start = 0;
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for (g = 0; g < ctx->num_bands[j]; g++) {
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minscale = ath(ctx->avctx->sample_rate * start / 1024.0, ATH_ADD);
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for (i = 1; i < ctx->bands[j][g]; i++)
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minscale = FFMIN(minscale, ath(ctx->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD));
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coeffs->ath[g] = minscale - minath;
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start += ctx->bands[j][g];
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}
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}
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pctx->ch = av_mallocz(sizeof(Psy3gppChannel) * ctx->avctx->channels);
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return 0;
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}
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/**
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* IIR filter used in block switching decision
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*/
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static float iir_filter(int in, float state[2])
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{
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float ret;
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ret = 0.7548f * (in - state[0]) + 0.5095f * state[1];
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state[0] = in;
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state[1] = ret;
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return ret;
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}
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/**
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* window grouping information stored as bits (0 - new group, 1 - group continues)
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*/
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static const uint8_t window_grouping[9] = {
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0xB6, 0x6C, 0xD8, 0xB2, 0x66, 0xC6, 0x96, 0x36, 0x36
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};
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/**
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* Tell encoder which window types to use.
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* @see 3GPP TS26.403 5.4.1 "Blockswitching"
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*/
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static FFPsyWindowInfo psy_3gpp_window(FFPsyContext *ctx,
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const int16_t *audio, const int16_t *la,
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int channel, int prev_type)
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{
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int i, j;
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int br = ctx->avctx->bit_rate / ctx->avctx->channels;
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int attack_ratio = br <= 16000 ? 18 : 10;
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Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
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Psy3gppChannel *pch = &pctx->ch[channel];
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uint8_t grouping = 0;
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FFPsyWindowInfo wi;
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memset(&wi, 0, sizeof(wi));
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if (la) {
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float s[8], v;
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int switch_to_eight = 0;
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float sum = 0.0, sum2 = 0.0;
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int attack_n = 0;
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for (i = 0; i < 8; i++) {
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for (j = 0; j < 128; j++) {
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v = iir_filter(la[(i*128+j)*ctx->avctx->channels], pch->iir_state);
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sum += v*v;
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}
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s[i] = sum;
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sum2 += sum;
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}
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for (i = 0; i < 8; i++) {
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if (s[i] > pch->win_energy * attack_ratio) {
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attack_n = i + 1;
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switch_to_eight = 1;
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break;
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}
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}
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pch->win_energy = pch->win_energy*7/8 + sum2/64;
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wi.window_type[1] = prev_type;
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switch (prev_type) {
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case ONLY_LONG_SEQUENCE:
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wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
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break;
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case LONG_START_SEQUENCE:
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wi.window_type[0] = EIGHT_SHORT_SEQUENCE;
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grouping = pch->next_grouping;
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break;
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case LONG_STOP_SEQUENCE:
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wi.window_type[0] = ONLY_LONG_SEQUENCE;
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break;
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case EIGHT_SHORT_SEQUENCE:
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wi.window_type[0] = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
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grouping = switch_to_eight ? pch->next_grouping : 0;
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break;
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}
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pch->next_grouping = window_grouping[attack_n];
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} else {
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for (i = 0; i < 3; i++)
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wi.window_type[i] = prev_type;
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grouping = (prev_type == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0;
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}
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wi.window_shape = 1;
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if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) {
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wi.num_windows = 1;
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wi.grouping[0] = 1;
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} else {
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int lastgrp = 0;
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wi.num_windows = 8;
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for (i = 0; i < 8; i++) {
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if (!((grouping >> i) & 1))
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lastgrp = i;
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wi.grouping[lastgrp]++;
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}
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}
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return wi;
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}
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/**
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* Calculate band thresholds as suggested in 3GPP TS26.403
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*/
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static void psy_3gpp_analyze(FFPsyContext *ctx, int channel,
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const float *coefs, FFPsyWindowInfo *wi)
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{
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Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
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Psy3gppChannel *pch = &pctx->ch[channel];
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int start = 0;
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int i, w, g;
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const int num_bands = ctx->num_bands[wi->num_windows == 8];
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const uint8_t* band_sizes = ctx->bands[wi->num_windows == 8];
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Psy3gppCoeffs *coeffs = &pctx->psy_coef[wi->num_windows == 8];
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//calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
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for (w = 0; w < wi->num_windows*16; w += 16) {
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for (g = 0; g < num_bands; g++) {
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Psy3gppBand *band = &pch->band[w+g];
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band->energy = 0.0f;
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for (i = 0; i < band_sizes[g]; i++)
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band->energy += coefs[start+i] * coefs[start+i];
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band->energy *= 1.0f / (512*512);
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band->thr = band->energy * 0.001258925f;
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start += band_sizes[g];
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ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].energy = band->energy;
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}
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}
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//modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation"
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for (w = 0; w < wi->num_windows*16; w += 16) {
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Psy3gppBand *band = &pch->band[w];
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for (g = 1; g < num_bands; g++)
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band[g].thr = FFMAX(band[g].thr, band[g-1].thr * coeffs->spread_low[g-1]);
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for (g = num_bands - 2; g >= 0; g--)
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band[g].thr = FFMAX(band[g].thr, band[g+1].thr * coeffs->spread_hi [g]);
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for (g = 0; g < num_bands; g++) {
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band[g].thr_quiet = FFMAX(band[g].thr, coeffs->ath[g]);
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if (wi->num_windows != 8 && wi->window_type[1] != EIGHT_SHORT_SEQUENCE)
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band[g].thr_quiet = FFMAX(PSY_3GPP_RPEMIN*band[g].thr_quiet,
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FFMIN(band[g].thr_quiet,
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PSY_3GPP_RPELEV*pch->prev_band[w+g].thr_quiet));
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band[g].thr = FFMAX(band[g].thr, band[g].thr_quiet * 0.25);
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ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].threshold = band[g].thr;
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}
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}
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memcpy(pch->prev_band, pch->band, sizeof(pch->band));
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}
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static av_cold void psy_3gpp_end(FFPsyContext *apc)
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{
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Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
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av_freep(&pctx->ch);
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av_freep(&apc->model_priv_data);
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}
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const FFPsyModel ff_aac_psy_model =
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{
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.name = "3GPP TS 26.403-inspired model",
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.init = psy_3gpp_init,
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.window = psy_3gpp_window,
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.analyze = psy_3gpp_analyze,
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.end = psy_3gpp_end,
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};
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