libavcodec/lpc.c

   1 /**
   2  * LPC utility code
   3  * Copyright (c) 2006  Justin Ruggles <justin.ruggles@gmail.com>
   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 #include "libavutil/lls.h"
  23 #include "dsputil.h"
  24
  25 #define LPC_USE_DOUBLE
  26 #include "lpc.h"
  27
  28
  29 /**
  30  * Apply Welch window function to audio block
  31  */
  32 static void apply_welch_window(const int32_t *data, int len, double *w_data)
  33 {
  34     int i, n2;
  35     double w;
  36     double c;
  37
  38     assert(!(len&1)); //the optimization in r11881 does not support odd len
  39                       //if someone wants odd len extend the change in r11881
  40
  41     n2 = (len >> 1);
  42     c = 2.0 / (len - 1.0);
  43
  44     w_data+=n2;
  45       data+=n2;
  46     for(i=0; i<n2; i++) {
  47         w = c - n2 + i;
  48         w = 1.0 - (w * w);
  49         w_data[-i-1] = data[-i-1] * w;
  50         w_data[+i  ] = data[+i  ] * w;
  51     }
  52 }
  53
  54 /**
  55  * Calculates autocorrelation data from audio samples
  56  * A Welch window function is applied before calculation.
  57  */
  58 void ff_lpc_compute_autocorr(const int32_t *data, int len, int lag,
  59                              double *autoc)
  60 {
  61     int i, j;
  62     double tmp[len + lag + 1];
  63     double *data1= tmp + lag;
  64
  65     apply_welch_window(data, len, data1);
  66
  67     for(j=0; j<lag; j++)
  68         data1[j-lag]= 0.0;
  69     data1[len] = 0.0;
  70
  71     for(j=0; j<lag; j+=2){
  72         double sum0 = 1.0, sum1 = 1.0;
  73         for(i=j; i<len; i++){
  74             sum0 += data1[i] * data1[i-j];
  75             sum1 += data1[i] * data1[i-j-1];
  76         }
  77         autoc[j  ] = sum0;
  78         autoc[j+1] = sum1;
  79     }
  80
  81     if(j==lag){
  82         double sum = 1.0;
  83         for(i=j-1; i<len; i+=2){
  84             sum += data1[i  ] * data1[i-j  ]
  85                  + data1[i+1] * data1[i-j+1];
  86         }
  87         autoc[j] = sum;
  88     }
  89 }
  90
  91 /**
  92  * Quantize LPC coefficients
  93  */
  94 static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
  95                                int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
  96 {
  97     int i;
  98     double cmax, error;
  99     int32_t qmax;
 100     int sh;
 101
 102     /* define maximum levels */
 103     qmax = (1 << (precision - 1)) - 1;
 104
 105     /* find maximum coefficient value */
 106     cmax = 0.0;
 107     for(i=0; i<order; i++) {
 108         cmax= FFMAX(cmax, fabs(lpc_in[i]));
 109     }
 110
 111     /* if maximum value quantizes to zero, return all zeros */
 112     if(cmax * (1 << max_shift) < 1.0) {
 113         *shift = zero_shift;
 114         memset(lpc_out, 0, sizeof(int32_t) * order);
 115         return;
 116     }
 117
 118     /* calculate level shift which scales max coeff to available bits */
 119     sh = max_shift;
 120     while((cmax * (1 << sh) > qmax) && (sh > 0)) {
 121         sh--;
 122     }
 123
 124     /* since negative shift values are unsupported in decoder, scale down
 125        coefficients instead */
 126     if(sh == 0 && cmax > qmax) {
 127         double scale = ((double)qmax) / cmax;
 128         for(i=0; i<order; i++) {
 129             lpc_in[i] *= scale;
 130         }
 131     }
 132
 133     /* output quantized coefficients and level shift */
 134     error=0;
 135     for(i=0; i<order; i++) {
 136         error -= lpc_in[i] * (1 << sh);
 137         lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
 138         error -= lpc_out[i];
 139     }
 140     *shift = sh;
 141 }
 142
 143 static int estimate_best_order(double *ref, int min_order, int max_order)
 144 {
 145     int i, est;
 146
 147     est = min_order;
 148     for(i=max_order-1; i>=min_order-1; i--) {
 149         if(ref[i] > 0.10) {
 150             est = i+1;
 151             break;
 152         }
 153     }
 154     return est;
 155 }
 156
 157 /**
 158  * Calculate LPC coefficients for multiple orders
 159  *
 160  * @param use_lpc LPC method for determining coefficients
 161  * 0  = LPC with fixed pre-defined coeffs
 162  * 1  = LPC with coeffs determined by Levinson-Durbin recursion
 163  * 2+ = LPC with coeffs determined by Cholesky factorization using (use_lpc-1) passes.
 164  */
 165 int ff_lpc_calc_coefs(DSPContext *s,
 166                       const int32_t *samples, int blocksize, int min_order,
 167                       int max_order, int precision,
 168                       int32_t coefs[][MAX_LPC_ORDER], int *shift, int use_lpc,
 169                       int omethod, int max_shift, int zero_shift)
 170 {
 171     double autoc[MAX_LPC_ORDER+1];
 172     double ref[MAX_LPC_ORDER];
 173     double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
 174     int i, j, pass;
 175     int opt_order;
 176
 177     assert(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER && use_lpc > 0);
 178
 179     if(use_lpc == 1){
 180         s->lpc_compute_autocorr(samples, blocksize, max_order, autoc);
 181
 182         compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
 183
 184         for(i=0; i<max_order; i++)
 185             ref[i] = fabs(lpc[i][i]);
 186     }else{
 187         LLSModel m[2];
 188         double var[MAX_LPC_ORDER+1], av_uninit(weight);
 189
 190         for(pass=0; pass<use_lpc-1; pass++){
 191             av_init_lls(&m[pass&1], max_order);
 192
 193             weight=0;
 194             for(i=max_order; i<blocksize; i++){
 195                 for(j=0; j<=max_order; j++)
 196                     var[j]= samples[i-j];
 197
 198                 if(pass){
 199                     double eval, inv, rinv;
 200                     eval= av_evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
 201                     eval= (512>>pass) + fabs(eval - var[0]);
 202                     inv = 1/eval;
 203                     rinv = sqrt(inv);
 204                     for(j=0; j<=max_order; j++)
 205                         var[j] *= rinv;
 206                     weight += inv;
 207                 }else
 208                     weight++;
 209
 210                 av_update_lls(&m[pass&1], var, 1.0);
 211             }
 212             av_solve_lls(&m[pass&1], 0.001, 0);
 213         }
 214
 215         for(i=0; i<max_order; i++){
 216             for(j=0; j<max_order; j++)
 217                 lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
 218             ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
 219         }
 220         for(i=max_order-1; i>0; i--)
 221             ref[i] = ref[i-1] - ref[i];
 222     }
 223     opt_order = max_order;
 224
 225     if(omethod == ORDER_METHOD_EST) {
 226         opt_order = estimate_best_order(ref, min_order, max_order);
 227         i = opt_order-1;
 228         quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
 229     } else {
 230         for(i=min_order-1; i<max_order; i++) {
 231             quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
 232         }
 233     }
 234
 235     return opt_order;
 236 }