/* | |
** Copyright 2003-2010, VisualOn, Inc. | |
** | |
** Licensed under the Apache License, Version 2.0 (the "License"); | |
** you may not use this file except in compliance with the License. | |
** You may obtain a copy of the License at | |
** | |
** http://www.apache.org/licenses/LICENSE-2.0 | |
** | |
** Unless required by applicable law or agreed to in writing, software | |
** distributed under the License is distributed on an "AS IS" BASIS, | |
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
** See the License for the specific language governing permissions and | |
** limitations under the License. | |
*/ | |
/*********************************************************************** | |
* File: apisf_2s.c * | |
* * | |
* Description: Coding/Decodeing of ISF parameters with predication | |
* The ISF vector is quantized using two-stage VQ with split-by-2 * | |
* in 1st stage and split-by-5(or 3) in the second stage * | |
* * | |
************************************************************************/ | |
#include "typedef.h" | |
#include "basic_op.h" | |
#include "cnst.h" | |
#include "acelp.h" | |
#include "qpisf_2s.tab" /* Codebooks of isfs */ | |
#define MU 10923 /* Prediction factor (1.0/3.0) in Q15 */ | |
#define N_SURV_MAX 4 /* 4 survivors max */ | |
#define ALPHA 29491 /* 0. 9 in Q15 */ | |
#define ONE_ALPHA (32768-ALPHA) /* (1.0 - ALPHA) in Q15 */ | |
/* private functions */ | |
static void VQ_stage1( | |
Word16 * x, /* input : ISF residual vector */ | |
Word16 * dico, /* input : quantization codebook */ | |
Word16 dim, /* input : dimention of vector */ | |
Word16 dico_size, /* input : size of quantization codebook */ | |
Word16 * index, /* output: indices of survivors */ | |
Word16 surv /* input : number of survivor */ | |
); | |
/************************************************************************** | |
* Function: Qpisf_2s_46B() * | |
* * | |
* Description: Quantization of isf parameters with prediction. (46 bits) * | |
* * | |
* The isf vector is quantized using two-stage VQ with split-by-2 in * | |
* 1st stage and split-by-5 in the second stage. * | |
***************************************************************************/ | |
void Qpisf_2s_46b( | |
Word16 * isf1, /* (i) Q15 : ISF in the frequency domain (0..0.5) */ | |
Word16 * isf_q, /* (o) Q15 : quantized ISF (0..0.5) */ | |
Word16 * past_isfq, /* (io)Q15 : past ISF quantizer */ | |
Word16 * indice, /* (o) : quantization indices */ | |
Word16 nb_surv /* (i) : number of survivor (1, 2, 3 or 4) */ | |
) | |
{ | |
Word16 tmp_ind[5]; | |
Word16 surv1[N_SURV_MAX]; /* indices of survivors from 1st stage */ | |
Word32 i, k, temp, min_err, distance; | |
Word16 isf[ORDER]; | |
Word16 isf_stage2[ORDER]; | |
for (i = 0; i < ORDER; i++) | |
{ | |
isf[i] = vo_sub(isf1[i], mean_isf[i]); | |
isf[i] = vo_sub(isf[i], vo_mult(MU, past_isfq[i])); | |
} | |
VQ_stage1(&isf[0], dico1_isf, 9, SIZE_BK1, surv1, nb_surv); | |
distance = MAX_32; | |
for (k = 0; k < nb_surv; k++) | |
{ | |
for (i = 0; i < 9; i++) | |
{ | |
isf_stage2[i] = vo_sub(isf[i], dico1_isf[i + surv1[k] * 9]); | |
} | |
tmp_ind[0] = Sub_VQ(&isf_stage2[0], dico21_isf, 3, SIZE_BK21, &min_err); | |
temp = min_err; | |
tmp_ind[1] = Sub_VQ(&isf_stage2[3], dico22_isf, 3, SIZE_BK22, &min_err); | |
temp = vo_L_add(temp, min_err); | |
tmp_ind[2] = Sub_VQ(&isf_stage2[6], dico23_isf, 3, SIZE_BK23, &min_err); | |
temp = vo_L_add(temp, min_err); | |
if(temp < distance) | |
{ | |
distance = temp; | |
indice[0] = surv1[k]; | |
for (i = 0; i < 3; i++) | |
{ | |
indice[i + 2] = tmp_ind[i]; | |
} | |
} | |
} | |
VQ_stage1(&isf[9], dico2_isf, 7, SIZE_BK2, surv1, nb_surv); | |
distance = MAX_32; | |
for (k = 0; k < nb_surv; k++) | |
{ | |
for (i = 0; i < 7; i++) | |
{ | |
isf_stage2[i] = vo_sub(isf[9 + i], dico2_isf[i + surv1[k] * 7]); | |
} | |
tmp_ind[0] = Sub_VQ(&isf_stage2[0], dico24_isf, 3, SIZE_BK24, &min_err); | |
temp = min_err; | |
tmp_ind[1] = Sub_VQ(&isf_stage2[3], dico25_isf, 4, SIZE_BK25, &min_err); | |
temp = vo_L_add(temp, min_err); | |
if(temp < distance) | |
{ | |
distance = temp; | |
indice[1] = surv1[k]; | |
for (i = 0; i < 2; i++) | |
{ | |
indice[i + 5] = tmp_ind[i]; | |
} | |
} | |
} | |
Dpisf_2s_46b(indice, isf_q, past_isfq, isf_q, isf_q, 0, 0); | |
return; | |
} | |
/***************************************************************************** | |
* Function: Qpisf_2s_36B() * | |
* * | |
* Description: Quantization of isf parameters with prediction. (36 bits) * | |
* * | |
* The isf vector is quantized using two-stage VQ with split-by-2 in * | |
* 1st stage and split-by-3 in the second stage. * | |
******************************************************************************/ | |
void Qpisf_2s_36b( | |
Word16 * isf1, /* (i) Q15 : ISF in the frequency domain (0..0.5) */ | |
Word16 * isf_q, /* (o) Q15 : quantized ISF (0..0.5) */ | |
Word16 * past_isfq, /* (io)Q15 : past ISF quantizer */ | |
Word16 * indice, /* (o) : quantization indices */ | |
Word16 nb_surv /* (i) : number of survivor (1, 2, 3 or 4) */ | |
) | |
{ | |
Word16 i, k, tmp_ind[5]; | |
Word16 surv1[N_SURV_MAX]; /* indices of survivors from 1st stage */ | |
Word32 temp, min_err, distance; | |
Word16 isf[ORDER]; | |
Word16 isf_stage2[ORDER]; | |
for (i = 0; i < ORDER; i++) | |
{ | |
isf[i] = vo_sub(isf1[i], mean_isf[i]); | |
isf[i] = vo_sub(isf[i], vo_mult(MU, past_isfq[i])); | |
} | |
VQ_stage1(&isf[0], dico1_isf, 9, SIZE_BK1, surv1, nb_surv); | |
distance = MAX_32; | |
for (k = 0; k < nb_surv; k++) | |
{ | |
for (i = 0; i < 9; i++) | |
{ | |
isf_stage2[i] = vo_sub(isf[i], dico1_isf[i + surv1[k] * 9]); | |
} | |
tmp_ind[0] = Sub_VQ(&isf_stage2[0], dico21_isf_36b, 5, SIZE_BK21_36b, &min_err); | |
temp = min_err; | |
tmp_ind[1] = Sub_VQ(&isf_stage2[5], dico22_isf_36b, 4, SIZE_BK22_36b, &min_err); | |
temp = vo_L_add(temp, min_err); | |
if(temp < distance) | |
{ | |
distance = temp; | |
indice[0] = surv1[k]; | |
for (i = 0; i < 2; i++) | |
{ | |
indice[i + 2] = tmp_ind[i]; | |
} | |
} | |
} | |
VQ_stage1(&isf[9], dico2_isf, 7, SIZE_BK2, surv1, nb_surv); | |
distance = MAX_32; | |
for (k = 0; k < nb_surv; k++) | |
{ | |
for (i = 0; i < 7; i++) | |
{ | |
isf_stage2[i] = vo_sub(isf[9 + i], dico2_isf[i + surv1[k] * 7]); | |
} | |
tmp_ind[0] = Sub_VQ(&isf_stage2[0], dico23_isf_36b, 7, SIZE_BK23_36b, &min_err); | |
temp = min_err; | |
if(temp < distance) | |
{ | |
distance = temp; | |
indice[1] = surv1[k]; | |
indice[4] = tmp_ind[0]; | |
} | |
} | |
Dpisf_2s_36b(indice, isf_q, past_isfq, isf_q, isf_q, 0, 0); | |
return; | |
} | |
/********************************************************************* | |
* Function: Dpisf_2s_46b() * | |
* * | |
* Description: Decoding of ISF parameters * | |
**********************************************************************/ | |
void Dpisf_2s_46b( | |
Word16 * indice, /* input: quantization indices */ | |
Word16 * isf_q, /* output: quantized ISF in frequency domain (0..0.5) */ | |
Word16 * past_isfq, /* i/0 : past ISF quantizer */ | |
Word16 * isfold, /* input : past quantized ISF */ | |
Word16 * isf_buf, /* input : isf buffer */ | |
Word16 bfi, /* input : Bad frame indicator */ | |
Word16 enc_dec | |
) | |
{ | |
Word16 ref_isf[M], tmp; | |
Word32 i, j, L_tmp; | |
if (bfi == 0) /* Good frame */ | |
{ | |
for (i = 0; i < 9; i++) | |
{ | |
isf_q[i] = dico1_isf[indice[0] * 9 + i]; | |
} | |
for (i = 0; i < 7; i++) | |
{ | |
isf_q[i + 9] = dico2_isf[indice[1] * 7 + i]; | |
} | |
for (i = 0; i < 3; i++) | |
{ | |
isf_q[i] = add1(isf_q[i], dico21_isf[indice[2] * 3 + i]); | |
isf_q[i + 3] = add1(isf_q[i + 3], dico22_isf[indice[3] * 3 + i]); | |
isf_q[i + 6] = add1(isf_q[i + 6], dico23_isf[indice[4] * 3 + i]); | |
isf_q[i + 9] = add1(isf_q[i + 9], dico24_isf[indice[5] * 3 + i]); | |
} | |
for (i = 0; i < 4; i++) | |
{ | |
isf_q[i + 12] = add1(isf_q[i + 12], dico25_isf[indice[6] * 4 + i]); | |
} | |
for (i = 0; i < ORDER; i++) | |
{ | |
tmp = isf_q[i]; | |
isf_q[i] = add1(tmp, mean_isf[i]); | |
isf_q[i] = add1(isf_q[i], vo_mult(MU, past_isfq[i])); | |
past_isfq[i] = tmp; | |
} | |
if (enc_dec) | |
{ | |
for (i = 0; i < M; i++) | |
{ | |
for (j = (L_MEANBUF - 1); j > 0; j--) | |
{ | |
isf_buf[j * M + i] = isf_buf[(j - 1) * M + i]; | |
} | |
isf_buf[i] = isf_q[i]; | |
} | |
} | |
} else | |
{ /* bad frame */ | |
for (i = 0; i < M; i++) | |
{ | |
L_tmp = mean_isf[i] << 14; | |
for (j = 0; j < L_MEANBUF; j++) | |
{ | |
L_tmp += (isf_buf[j * M + i] << 14); | |
} | |
ref_isf[i] = vo_round(L_tmp); | |
} | |
/* use the past ISFs slightly shifted towards their mean */ | |
for (i = 0; i < ORDER; i++) | |
{ | |
isf_q[i] = add1(vo_mult(ALPHA, isfold[i]), vo_mult(ONE_ALPHA, ref_isf[i])); | |
} | |
/* estimate past quantized residual to be used in next frame */ | |
for (i = 0; i < ORDER; i++) | |
{ | |
tmp = add1(ref_isf[i], vo_mult(past_isfq[i], MU)); /* predicted ISF */ | |
past_isfq[i] = vo_sub(isf_q[i], tmp); | |
past_isfq[i] = (past_isfq[i] >> 1); /* past_isfq[i] *= 0.5 */ | |
} | |
} | |
Reorder_isf(isf_q, ISF_GAP, ORDER); | |
return; | |
} | |
/********************************************************************* | |
* Function: Disf_2s_36b() * | |
* * | |
* Description: Decoding of ISF parameters * | |
*********************************************************************/ | |
void Dpisf_2s_36b( | |
Word16 * indice, /* input: quantization indices */ | |
Word16 * isf_q, /* output: quantized ISF in frequency domain (0..0.5) */ | |
Word16 * past_isfq, /* i/0 : past ISF quantizer */ | |
Word16 * isfold, /* input : past quantized ISF */ | |
Word16 * isf_buf, /* input : isf buffer */ | |
Word16 bfi, /* input : Bad frame indicator */ | |
Word16 enc_dec | |
) | |
{ | |
Word16 ref_isf[M], tmp; | |
Word32 i, j, L_tmp; | |
if (bfi == 0) /* Good frame */ | |
{ | |
for (i = 0; i < 9; i++) | |
{ | |
isf_q[i] = dico1_isf[indice[0] * 9 + i]; | |
} | |
for (i = 0; i < 7; i++) | |
{ | |
isf_q[i + 9] = dico2_isf[indice[1] * 7 + i]; | |
} | |
for (i = 0; i < 5; i++) | |
{ | |
isf_q[i] = add1(isf_q[i], dico21_isf_36b[indice[2] * 5 + i]); | |
} | |
for (i = 0; i < 4; i++) | |
{ | |
isf_q[i + 5] = add1(isf_q[i + 5], dico22_isf_36b[indice[3] * 4 + i]); | |
} | |
for (i = 0; i < 7; i++) | |
{ | |
isf_q[i + 9] = add1(isf_q[i + 9], dico23_isf_36b[indice[4] * 7 + i]); | |
} | |
for (i = 0; i < ORDER; i++) | |
{ | |
tmp = isf_q[i]; | |
isf_q[i] = add1(tmp, mean_isf[i]); | |
isf_q[i] = add1(isf_q[i], vo_mult(MU, past_isfq[i])); | |
past_isfq[i] = tmp; | |
} | |
if (enc_dec) | |
{ | |
for (i = 0; i < M; i++) | |
{ | |
for (j = (L_MEANBUF - 1); j > 0; j--) | |
{ | |
isf_buf[j * M + i] = isf_buf[(j - 1) * M + i]; | |
} | |
isf_buf[i] = isf_q[i]; | |
} | |
} | |
} else | |
{ /* bad frame */ | |
for (i = 0; i < M; i++) | |
{ | |
L_tmp = (mean_isf[i] << 14); | |
for (j = 0; j < L_MEANBUF; j++) | |
{ | |
L_tmp += (isf_buf[j * M + i] << 14); | |
} | |
ref_isf[i] = vo_round(L_tmp); | |
} | |
/* use the past ISFs slightly shifted towards their mean */ | |
for (i = 0; i < ORDER; i++) | |
{ | |
isf_q[i] = add1(vo_mult(ALPHA, isfold[i]), vo_mult(ONE_ALPHA, ref_isf[i])); | |
} | |
/* estimate past quantized residual to be used in next frame */ | |
for (i = 0; i < ORDER; i++) | |
{ | |
tmp = add1(ref_isf[i], vo_mult(past_isfq[i], MU)); /* predicted ISF */ | |
past_isfq[i] = vo_sub(isf_q[i], tmp); | |
past_isfq[i] = past_isfq[i] >> 1; /* past_isfq[i] *= 0.5 */ | |
} | |
} | |
Reorder_isf(isf_q, ISF_GAP, ORDER); | |
return; | |
} | |
/*************************************************************************** | |
* Function: Reorder_isf() * | |
* * | |
* Description: To make sure that the isfs are properly order and to * | |
* keep a certain minimum distance between consecutive isfs. * | |
*--------------------------------------------------------------------------* | |
* Argument description in/out * | |
* * | |
* isf[] vector of isfs i/o * | |
* min_dist minimum required distance i * | |
* n LPC order i * | |
****************************************************************************/ | |
void Reorder_isf( | |
Word16 * isf, /* (i/o) Q15: ISF in the frequency domain (0..0.5) */ | |
Word16 min_dist, /* (i) Q15 : minimum distance to keep */ | |
Word16 n /* (i) : number of ISF */ | |
) | |
{ | |
Word32 i; | |
Word16 isf_min; | |
isf_min = min_dist; | |
for (i = 0; i < n - 1; i++) | |
{ | |
if(isf[i] < isf_min) | |
{ | |
isf[i] = isf_min; | |
} | |
isf_min = (isf[i] + min_dist); | |
} | |
return; | |
} | |
Word16 Sub_VQ( /* output: return quantization index */ | |
Word16 * x, /* input : ISF residual vector */ | |
Word16 * dico, /* input : quantization codebook */ | |
Word16 dim, /* input : dimention of vector */ | |
Word16 dico_size, /* input : size of quantization codebook */ | |
Word32 * distance /* output: error of quantization */ | |
) | |
{ | |
Word16 temp, *p_dico; | |
Word32 i, j, index; | |
Word32 dist_min, dist; | |
dist_min = MAX_32; | |
p_dico = dico; | |
index = 0; | |
for (i = 0; i < dico_size; i++) | |
{ | |
dist = 0; | |
for (j = 0; j < dim; j++) | |
{ | |
temp = x[j] - (*p_dico++); | |
dist += (temp * temp)<<1; | |
} | |
if(dist < dist_min) | |
{ | |
dist_min = dist; | |
index = i; | |
} | |
} | |
*distance = dist_min; | |
/* Reading the selected vector */ | |
p_dico = &dico[index * dim]; | |
for (j = 0; j < dim; j++) | |
{ | |
x[j] = *p_dico++; | |
} | |
return index; | |
} | |
static void VQ_stage1( | |
Word16 * x, /* input : ISF residual vector */ | |
Word16 * dico, /* input : quantization codebook */ | |
Word16 dim, /* input : dimention of vector */ | |
Word16 dico_size, /* input : size of quantization codebook */ | |
Word16 * index, /* output: indices of survivors */ | |
Word16 surv /* input : number of survivor */ | |
) | |
{ | |
Word16 temp, *p_dico; | |
Word32 i, j, k, l; | |
Word32 dist_min[N_SURV_MAX], dist; | |
dist_min[0] = MAX_32; | |
dist_min[1] = MAX_32; | |
dist_min[2] = MAX_32; | |
dist_min[3] = MAX_32; | |
index[0] = 0; | |
index[1] = 1; | |
index[2] = 2; | |
index[3] = 3; | |
p_dico = dico; | |
for (i = 0; i < dico_size; i++) | |
{ | |
dist = 0; | |
for (j = 0; j < dim; j++) | |
{ | |
temp = x[j] - (*p_dico++); | |
dist += (temp * temp)<<1; | |
} | |
for (k = 0; k < surv; k++) | |
{ | |
if(dist < dist_min[k]) | |
{ | |
for (l = surv - 1; l > k; l--) | |
{ | |
dist_min[l] = dist_min[l - 1]; | |
index[l] = index[l - 1]; | |
} | |
dist_min[k] = dist; | |
index[k] = i; | |
break; | |
} | |
} | |
} | |
return; | |
} | |