libavcodec/aacpsy.c

   1 /*
   2  * AAC encoder psychoacoustic model
   3  * Copyright (C) 2008 Konstantin Shishkov
   4  *
   5  * This file is part of FFmpeg.
   6  *
   7  * FFmpeg is free software; you can redistribute it and/or
   8  * modify it under the terms of the GNU Lesser General Public
   9  * License as published by the Free Software Foundation; either
  10  * version 2.1 of the License, or (at your option) any later version.
  11  *
  12  * FFmpeg is distributed in the hope that it will be useful,
  13  * but WITHOUT ANY WARRANTY; without even the implied warranty of
  14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  15  * Lesser General Public License for more details.
  16  *
  17  * You should have received a copy of the GNU Lesser General Public
  18  * License along with FFmpeg; if not, write to the Free Software
  19  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
  20  */
  21
  22 /**
  23  * @file libavcodec/aacpsy.c
  24  * AAC encoder psychoacoustic model
  25  */
  26
  27 #include "avcodec.h"
  28 #include "aactab.h"
  29 #include "psymodel.h"
  30
  31 /***********************************
  32  *              TODOs:
  33  * thresholds linearization after their modifications for attaining given bitrate
  34  * try other bitrate controlling mechanism (maybe use ratecontrol.c?)
  35  * control quality for quality-based output
  36  **********************************/
  37
  38 /**
  39  * constants for 3GPP AAC psychoacoustic model
  40  * @{
  41  */
  42 #define PSY_3GPP_SPREAD_LOW  1.5f // spreading factor for ascending threshold spreading  (15 dB/Bark)
  43 #define PSY_3GPP_SPREAD_HI   3.0f // spreading factor for descending threshold spreading (30 dB/Bark)
  44
  45 #define PSY_3GPP_RPEMIN      0.01f
  46 #define PSY_3GPP_RPELEV      2.0f
  47 /**
  48  * @}
  49  */
  50
  51 /**
  52  * information for single band used by 3GPP TS26.403-inspired psychoacoustic model
  53  */
  54 typedef struct Psy3gppBand{
  55     float energy;    ///< band energy
  56     float ffac;      ///< form factor
  57     float thr;       ///< energy threshold
  58     float min_snr;   ///< minimal SNR
  59     float thr_quiet; ///< threshold in quiet
  60 }Psy3gppBand;
  61
  62 /**
  63  * single/pair channel context for psychoacoustic model
  64  */
  65 typedef struct Psy3gppChannel{
  66     Psy3gppBand band[128];               ///< bands information
  67     Psy3gppBand prev_band[128];          ///< bands information from the previous frame
  68
  69     float       win_energy;              ///< sliding average of channel energy
  70     float       iir_state[2];            ///< hi-pass IIR filter state
  71     uint8_t     next_grouping;           ///< stored grouping scheme for the next frame (in case of 8 short window sequence)
  72     enum WindowSequence next_window_seq; ///< window sequence to be used in the next frame
  73 }Psy3gppChannel;
  74
  75 /**
  76  * psychoacoustic model frame type-dependent coefficients
  77  */
  78 typedef struct Psy3gppCoeffs{
  79     float ath       [64]; ///< absolute threshold of hearing per bands
  80     float barks     [64]; ///< Bark value for each spectral band in long frame
  81     float spread_low[64]; ///< spreading factor for low-to-high threshold spreading in long frame
  82     float spread_hi [64]; ///< spreading factor for high-to-low threshold spreading in long frame
  83 }Psy3gppCoeffs;
  84
  85 /**
  86  * 3GPP TS26.403-inspired psychoacoustic model specific data
  87  */
  88 typedef struct Psy3gppContext{
  89     Psy3gppCoeffs psy_coef[2];
  90     Psy3gppChannel *ch;
  91 }Psy3gppContext;
  92
  93 /**
  94  * Calculate Bark value for given line.
  95  */
  96 static av_cold float calc_bark(float f)
  97 {
  98     return 13.3f * atanf(0.00076f * f) + 3.5f * atanf((f / 7500.0f) * (f / 7500.0f));
  99 }
 100
 101 #define ATH_ADD 4
 102 /**
 103  * Calculate ATH value for given frequency.
 104  * Borrowed from Lame.
 105  */
 106 static av_cold float ath(float f, float add)
 107 {
 108     f /= 1000.0f;
 109     return    3.64 * pow(f, -0.8)
 110             - 6.8  * exp(-0.6  * (f - 3.4) * (f - 3.4))
 111             + 6.0  * exp(-0.15 * (f - 8.7) * (f - 8.7))
 112             + (0.6 + 0.04 * add) * 0.001 * f * f * f * f;
 113 }
 114
 115 static av_cold int psy_3gpp_init(FFPsyContext *ctx) {
 116     Psy3gppContext *pctx;
 117     float barks[1024];
 118     int i, j, g, start;
 119     float prev, minscale, minath;
 120
 121     ctx->model_priv_data = av_mallocz(sizeof(Psy3gppContext));
 122     pctx = (Psy3gppContext*) ctx->model_priv_data;
 123
 124     for (i = 0; i < 1024; i++)
 125         barks[i] = calc_bark(i * ctx->avctx->sample_rate / 2048.0);
 126     minath = ath(3410, ATH_ADD);
 127     for (j = 0; j < 2; j++) {
 128         Psy3gppCoeffs *coeffs = &pctx->psy_coef[j];
 129         i = 0;
 130         prev = 0.0;
 131         for (g = 0; g < ctx->num_bands[j]; g++) {
 132             i += ctx->bands[j][g];
 133             coeffs->barks[g] = (barks[i - 1] + prev) / 2.0;
 134             prev = barks[i - 1];
 135         }
 136         for (g = 0; g < ctx->num_bands[j] - 1; g++) {
 137             coeffs->spread_low[g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_LOW);
 138             coeffs->spread_hi [g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_HI);
 139         }
 140         start = 0;
 141         for (g = 0; g < ctx->num_bands[j]; g++) {
 142             minscale = ath(ctx->avctx->sample_rate * start / 1024.0, ATH_ADD);
 143             for (i = 1; i < ctx->bands[j][g]; i++)
 144                 minscale = FFMIN(minscale, ath(ctx->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD));
 145             coeffs->ath[g] = minscale - minath;
 146             start += ctx->bands[j][g];
 147         }
 148     }
 149
 150     pctx->ch = av_mallocz(sizeof(Psy3gppChannel) * ctx->avctx->channels);
 151     return 0;
 152 }
 153
 154 /**
 155  * IIR filter used in block switching decision
 156  */
 157 static float iir_filter(int in, float state[2])
 158 {
 159     float ret;
 160
 161     ret = 0.7548f * (in - state[0]) + 0.5095f * state[1];
 162     state[0] = in;
 163     state[1] = ret;
 164     return ret;
 165 }
 166
 167 /**
 168  * window grouping information stored as bits (0 - new group, 1 - group continues)
 169  */
 170 static const uint8_t window_grouping[9] = {
 171     0xB6, 0x6C, 0xD8, 0xB2, 0x66, 0xC6, 0x96, 0x36, 0x36
 172 };
 173
 174 /**
 175  * Tell encoder which window types to use.
 176  * @see 3GPP TS26.403 5.4.1 "Blockswitching"
 177  */
 178 static FFPsyWindowInfo psy_3gpp_window(FFPsyContext *ctx,
 179                                        const int16_t *audio, const int16_t *la,
 180                                        int channel, int prev_type)
 181 {
 182     int i, j;
 183     int br               = ctx->avctx->bit_rate / ctx->avctx->channels;
 184     int attack_ratio     = br <= 16000 ? 18 : 10;
 185     Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
 186     Psy3gppChannel *pch  = &pctx->ch[channel];
 187     uint8_t grouping     = 0;
 188     FFPsyWindowInfo wi;
 189
 190     memset(&wi, 0, sizeof(wi));
 191     if (la) {
 192         float s[8], v;
 193         int switch_to_eight = 0;
 194         float sum = 0.0, sum2 = 0.0;
 195         int attack_n = 0;
 196         for (i = 0; i < 8; i++) {
 197             for (j = 0; j < 128; j++) {
 198                 v = iir_filter(audio[(i*128+j)*ctx->avctx->channels], pch->iir_state);
 199                 sum += v*v;
 200             }
 201             s[i]  = sum;
 202             sum2 += sum;
 203         }
 204         for (i = 0; i < 8; i++) {
 205             if (s[i] > pch->win_energy * attack_ratio) {
 206                 attack_n        = i + 1;
 207                 switch_to_eight = 1;
 208                 break;
 209             }
 210         }
 211         pch->win_energy = pch->win_energy*7/8 + sum2/64;
 212
 213         wi.window_type[1] = prev_type;
 214         switch (prev_type) {
 215         case ONLY_LONG_SEQUENCE:
 216             wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
 217             break;
 218         case LONG_START_SEQUENCE:
 219             wi.window_type[0] = EIGHT_SHORT_SEQUENCE;
 220             grouping = pch->next_grouping;
 221             break;
 222         case LONG_STOP_SEQUENCE:
 223             wi.window_type[0] = ONLY_LONG_SEQUENCE;
 224             break;
 225         case EIGHT_SHORT_SEQUENCE:
 226             wi.window_type[0] = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
 227             grouping = switch_to_eight ? pch->next_grouping : 0;
 228             break;
 229         }
 230         pch->next_grouping = window_grouping[attack_n];
 231     } else {
 232         for (i = 0; i < 3; i++)
 233             wi.window_type[i] = prev_type;
 234         grouping = (prev_type == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0;
 235     }
 236
 237     wi.window_shape   = 1;
 238     if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) {
 239         wi.num_windows = 1;
 240         wi.grouping[0] = 1;
 241     } else {
 242         int lastgrp = 0;
 243         wi.num_windows = 8;
 244         for (i = 0; i < 8; i++) {
 245             if (!((grouping >> i) & 1))
 246                 lastgrp = i;
 247             wi.grouping[lastgrp]++;
 248         }
 249     }
 250
 251     return wi;
 252 }
 253
 254 /**
 255  * Calculate band thresholds as suggested in 3GPP TS26.403
 256  */
 257 static void psy_3gpp_analyze(FFPsyContext *ctx, int channel,
 258                              const float *coefs, FFPsyWindowInfo *wi)
 259 {
 260     Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data;
 261     Psy3gppChannel *pch  = &pctx->ch[channel];
 262     int start = 0;
 263     int i, w, g;
 264     const int num_bands       = ctx->num_bands[wi->num_windows == 8];
 265     const uint8_t* band_sizes = ctx->bands[wi->num_windows == 8];
 266     Psy3gppCoeffs *coeffs     = &pctx->psy_coef[wi->num_windows == 8];
 267
 268     //calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
 269     for (w = 0; w < wi->num_windows*16; w += 16) {
 270         for (g = 0; g < num_bands; g++) {
 271             Psy3gppBand *band = &pch->band[w+g];
 272             band->energy = 0.0f;
 273             for (i = 0; i < band_sizes[g]; i++)
 274                 band->energy += coefs[start+i] * coefs[start+i];
 275             band->energy *= 1.0f / (512*512);
 276             band->thr     = band->energy * 0.001258925f;
 277             start        += band_sizes[g];
 278
 279             ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].energy = band->energy;
 280         }
 281     }
 282     //modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation"
 283     for (w = 0; w < wi->num_windows*16; w += 16) {
 284         Psy3gppBand *band = &pch->band[w];
 285         for (g = 1; g < num_bands; g++)
 286             band[g].thr = FFMAX(band[g].thr, band[g-1].thr * coeffs->spread_low[g-1]);
 287         for (g = num_bands - 2; g >= 0; g--)
 288             band[g].thr = FFMAX(band[g].thr, band[g+1].thr * coeffs->spread_hi [g]);
 289         for (g = 0; g < num_bands; g++) {
 290             band[g].thr_quiet = FFMAX(band[g].thr, coeffs->ath[g]);
 291             if (wi->num_windows != 8 && wi->window_type[1] != EIGHT_SHORT_SEQUENCE)
 292                 band[g].thr_quiet = FFMAX(PSY_3GPP_RPEMIN*band[g].thr_quiet,
 293                                           FFMIN(band[g].thr_quiet,
 294                                           PSY_3GPP_RPELEV*pch->prev_band[w+g].thr_quiet));
 295             band[g].thr = FFMAX(band[g].thr, band[g].thr_quiet * 0.25);
 296
 297             ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].threshold = band[g].thr;
 298         }
 299     }
 300     memcpy(pch->prev_band, pch->band, sizeof(pch->band));
 301 }
 302
 303 static av_cold void psy_3gpp_end(FFPsyContext *apc)
 304 {
 305     Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data;
 306     av_freep(&pctx->ch);
 307     av_freep(&apc->model_priv_data);
 308 }
 309
 310
 311 const FFPsyModel ff_aac_psy_model =
 312 {
 313     .name    = "3GPP TS 26.403-inspired model",
 314     .init    = psy_3gpp_init,
 315     .window  = psy_3gpp_window,
 316     .analyze = psy_3gpp_analyze,
 317     .end     = psy_3gpp_end,
 318 };