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23940f1405
Add AVLPCType enum. Deprecate AVCodecContext.use_lpc. Originally committed as revision 24199 to svn://svn.ffmpeg.org/ffmpeg/trunk
239 lines
6.8 KiB
C
239 lines
6.8 KiB
C
/**
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* LPC utility code
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* Copyright (c) 2006 Justin Ruggles <justin.ruggles@gmail.com>
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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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#include "libavutil/lls.h"
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#include "dsputil.h"
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#define LPC_USE_DOUBLE
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#include "lpc.h"
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/**
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* Apply Welch window function to audio block
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*/
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static void apply_welch_window(const int32_t *data, int len, double *w_data)
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{
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int i, n2;
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double w;
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double c;
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assert(!(len&1)); //the optimization in r11881 does not support odd len
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//if someone wants odd len extend the change in r11881
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n2 = (len >> 1);
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c = 2.0 / (len - 1.0);
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w_data+=n2;
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data+=n2;
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for(i=0; i<n2; i++) {
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w = c - n2 + i;
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w = 1.0 - (w * w);
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w_data[-i-1] = data[-i-1] * w;
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w_data[+i ] = data[+i ] * w;
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}
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}
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/**
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* Calculate autocorrelation data from audio samples
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* A Welch window function is applied before calculation.
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*/
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void ff_lpc_compute_autocorr(const int32_t *data, int len, int lag,
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double *autoc)
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{
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int i, j;
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double tmp[len + lag + 1];
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double *data1= tmp + lag;
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apply_welch_window(data, len, data1);
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for(j=0; j<lag; j++)
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data1[j-lag]= 0.0;
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data1[len] = 0.0;
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for(j=0; j<lag; j+=2){
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double sum0 = 1.0, sum1 = 1.0;
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for(i=j; i<len; i++){
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sum0 += data1[i] * data1[i-j];
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sum1 += data1[i] * data1[i-j-1];
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}
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autoc[j ] = sum0;
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autoc[j+1] = sum1;
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}
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if(j==lag){
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double sum = 1.0;
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for(i=j-1; i<len; i+=2){
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sum += data1[i ] * data1[i-j ]
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+ data1[i+1] * data1[i-j+1];
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}
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autoc[j] = sum;
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}
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}
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/**
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* Quantize LPC coefficients
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*/
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static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
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int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
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{
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int i;
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double cmax, error;
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int32_t qmax;
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int sh;
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/* define maximum levels */
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qmax = (1 << (precision - 1)) - 1;
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/* find maximum coefficient value */
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cmax = 0.0;
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for(i=0; i<order; i++) {
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cmax= FFMAX(cmax, fabs(lpc_in[i]));
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}
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/* if maximum value quantizes to zero, return all zeros */
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if(cmax * (1 << max_shift) < 1.0) {
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*shift = zero_shift;
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memset(lpc_out, 0, sizeof(int32_t) * order);
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return;
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}
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/* calculate level shift which scales max coeff to available bits */
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sh = max_shift;
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while((cmax * (1 << sh) > qmax) && (sh > 0)) {
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sh--;
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}
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/* since negative shift values are unsupported in decoder, scale down
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coefficients instead */
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if(sh == 0 && cmax > qmax) {
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double scale = ((double)qmax) / cmax;
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for(i=0; i<order; i++) {
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lpc_in[i] *= scale;
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}
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}
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/* output quantized coefficients and level shift */
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error=0;
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for(i=0; i<order; i++) {
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error -= lpc_in[i] * (1 << sh);
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lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
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error -= lpc_out[i];
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}
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*shift = sh;
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}
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static int estimate_best_order(double *ref, int min_order, int max_order)
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{
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int i, est;
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est = min_order;
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for(i=max_order-1; i>=min_order-1; i--) {
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if(ref[i] > 0.10) {
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est = i+1;
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break;
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}
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}
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return est;
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}
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/**
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* Calculate LPC coefficients for multiple orders
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*
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* @param use_lpc LPC method for determining coefficients
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* 0 = LPC with fixed pre-defined coeffs
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* 1 = LPC with coeffs determined by Levinson-Durbin recursion
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* 2+ = LPC with coeffs determined by Cholesky factorization using (use_lpc-1) passes.
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*/
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int ff_lpc_calc_coefs(DSPContext *s,
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const int32_t *samples, int blocksize, int min_order,
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int max_order, int precision,
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int32_t coefs[][MAX_LPC_ORDER], int *shift,
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enum AVLPCType lpc_type, int lpc_passes,
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int omethod, int max_shift, int zero_shift)
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{
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double autoc[MAX_LPC_ORDER+1];
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double ref[MAX_LPC_ORDER];
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double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
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int i, j, pass;
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int opt_order;
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assert(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER &&
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lpc_type > AV_LPC_TYPE_FIXED);
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if (lpc_type == AV_LPC_TYPE_LEVINSON) {
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s->lpc_compute_autocorr(samples, blocksize, max_order, autoc);
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compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
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for(i=0; i<max_order; i++)
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ref[i] = fabs(lpc[i][i]);
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} else if (lpc_type == AV_LPC_TYPE_CHOLESKY) {
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LLSModel m[2];
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double var[MAX_LPC_ORDER+1], av_uninit(weight);
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for(pass=0; pass<lpc_passes; pass++){
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av_init_lls(&m[pass&1], max_order);
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weight=0;
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for(i=max_order; i<blocksize; i++){
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for(j=0; j<=max_order; j++)
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var[j]= samples[i-j];
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if(pass){
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double eval, inv, rinv;
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eval= av_evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
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eval= (512>>pass) + fabs(eval - var[0]);
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inv = 1/eval;
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rinv = sqrt(inv);
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for(j=0; j<=max_order; j++)
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var[j] *= rinv;
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weight += inv;
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}else
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weight++;
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av_update_lls(&m[pass&1], var, 1.0);
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}
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av_solve_lls(&m[pass&1], 0.001, 0);
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}
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for(i=0; i<max_order; i++){
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for(j=0; j<max_order; j++)
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lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
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ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
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}
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for(i=max_order-1; i>0; i--)
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ref[i] = ref[i-1] - ref[i];
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}
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opt_order = max_order;
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if(omethod == ORDER_METHOD_EST) {
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opt_order = estimate_best_order(ref, min_order, max_order);
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i = opt_order-1;
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quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
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} else {
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for(i=min_order-1; i<max_order; i++) {
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quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
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}
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}
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return opt_order;
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}
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