Merge the AAC encoder from SoC svn. It is still considered experimental.

Originally committed as revision 19375 to svn://svn.ffmpeg.org/ffmpeg/trunk

1 files changed, 252 insertions, 34 deletions

diff --git a/libavcodec/aacpsy.c b/libavcodec/aacpsy.c
index 45fcad46be..3880266784 100644
--- a/libavcodec/aacpsy.c
+++ b/libavcodec/aacpsy.c
@@ -25,54 +25,25 @@
  */
 
 #include "avcodec.h"
-#include "aacpsy.h"
 #include "aactab.h"
+#include "psymodel.h"
 
 /***********************************
  *              TODOs:
- * General:
- * better audio preprocessing (add DC highpass filter?)
- * more psy models
- * maybe improve coefficient quantization function in some way
- *
- * 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);
-}
-
-static inline float get_approximate_quant_error(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;
-}
-
-/**
  * 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
 /**
  * @}
  */
@@ -83,9 +54,25 @@ static inline float get_approximate_quant_error(float *c, int size, int scale_id
 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{
@@ -96,9 +83,240 @@ typedef struct Psy3gppCoeffs{
 }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 inline float calc_bark(float f)
+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 = fminf(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(audio[(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 = fmaxf(PSY_3GPP_RPEMIN*band[g].thr_quiet,
+                                          fminf(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,
+};