/*
* Copyright (c) 2001-2016, Alliance for Open Media. All rights reserved
*
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at www.aomedia.org/license/software. If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
*/
/* clang-format off */
#ifdef HAVE_CONFIG_H
# include "config.h"
#endif
#include
#include "aom_dsp/bitwriter.h"
#include "av1/common/generic_code.h"
#include "av1/common/odintrin.h"
#include "pvq_encoder.h"
/** Encodes a value from 0 to N-1 (with N up to 16) based on a cdf and adapts
* the cdf accordingly.
*
* @param [in,out] w multi-symbol entropy encoder
* @param [in] val variable being encoded
* @param [in,out] cdf CDF of the variable (Q15)
* @param [in] n number of values possible
* @param [in,out] count number of symbols encoded with that cdf so far
* @param [in] rate adaptation rate shift (smaller is faster)
*/
void aom_encode_cdf_adapt_q15(aom_writer *w, int val, uint16_t *cdf, int n,
int *count, int rate) {
int i;
if (*count == 0) {
/* On the first call, we normalize the cdf to (32768 - n). This should
eventually be moved to the state init, but for now it makes it much
easier to experiment and convert symbols to the Q15 adaptation.*/
int ft;
ft = cdf[n - 1];
for (i = 0; i < n; i++) {
cdf[i] = cdf[i]*32768/ft;
}
}
aom_write_cdf(w, val, cdf, n);
aom_cdf_adapt_q15(val, cdf, n, count, rate);
}
/** Encodes a value from 0 to N-1 (with N up to 16) based on a cdf and adapts
* the cdf accordingly.
*
* @param [in,out] enc range encoder
* @param [in] val variable being encoded
* @param [in] cdf CDF of the variable (Q15)
* @param [in] n number of values possible
* @param [in] increment adaptation speed (Q15)
*/
void aom_encode_cdf_adapt(aom_writer *w, int val, uint16_t *cdf, int n,
int increment) {
int i;
aom_write_cdf_unscaled(w, val, cdf, n);
if (cdf[n-1] + increment > 32767) {
for (i = 0; i < n; i++) {
/* Second term ensures that the pdf is non-null */
cdf[i] = (cdf[i] >> 1) + i + 1;
}
}
for (i = val; i < n; i++) cdf[i] += increment;
}
/** Encodes a random variable using a "generic" model, assuming that the
* distribution is one-sided (zero and up), has a single mode, and decays
* exponentially past the model.
*
* @param [in,out] w multi-symbol entropy encoder
* @param [in,out] model generic probability model
* @param [in] x variable being encoded
* @param [in,out] ExQ16 expectation of x (adapted)
* @param [in] integration integration period of ExQ16 (leaky average over
* 1<> 1);
/* Choose the cdf to use: we have two per "octave" of ExQ16 */
id = OD_MINI(GENERIC_TABLES - 1, lg_q1);
cdf = model->cdf[id];
xs = (x + (1 << shift >> 1)) >> shift;
aom_write_symbol_pvq(w, OD_MINI(15, xs), cdf, 16);
if (xs >= 15) {
int e;
unsigned decay;
/* Estimate decay based on the assumption that the distribution is close
to Laplacian for large values. We should probably have an adaptive
estimate instead. Note: The 2* is a kludge that's not fully understood
yet. */
OD_ASSERT(*ex_q16 < INT_MAX >> 1);
e = ((2**ex_q16 >> 8) + (1 << shift >> 1)) >> shift;
decay = OD_MAXI(2, OD_MINI(254, 256*e/(e + 256)));
/* Encode the tail of the distribution assuming exponential decay. */
aom_laplace_encode_special(w, xs - 15, decay);
}
if (shift != 0) {
int special;
/* Because of the rounding, there's only half the number of possibilities
for xs=0. */
special = xs == 0;
if (shift - special > 0) {
aom_write_literal(w, x - (xs << shift) + (!special << (shift - 1)),
shift - special);
}
}
generic_model_update(ex_q16, x, integration);
OD_LOG((OD_LOG_ENTROPY_CODER, OD_LOG_DEBUG,
"enc: %d %d %d %d %d %x", *ex_q16, x, shift, id, xs, enc->rng));
}
/** Estimates the cost of encoding a value with generic_encode().
*
* @param [in,out] model generic probability model
* @param [in] x variable being encoded
* @param [in,out] ExQ16 expectation of x (adapted)
* @return number of bits (approximation)
*/
double generic_encode_cost(generic_encoder *model, int x, int *ex_q16) {
int lg_q1;
int shift;
int id;
uint16_t *cdf;
int xs;
int extra;
lg_q1 = log_ex(*ex_q16);
/* If expectation is too large, shift x to ensure that
all we have past xs=15 is the exponentially decaying tail
of the distribution */
shift = OD_MAXI(0, (lg_q1 - 5) >> 1);
/* Choose the cdf to use: we have two per "octave" of ExQ16 */
id = OD_MINI(GENERIC_TABLES - 1, lg_q1);
cdf = model->cdf[id];
xs = (x + (1 << shift >> 1)) >> shift;
extra = 0;
if (shift) extra = shift - (xs == 0);
xs = OD_MINI(15, xs);
/* Shortcut: assume it's going to cost 2 bits for the Laplace coder. */
if (xs == 15) extra += 2;
return
extra - OD_LOG2((double)(cdf[xs] - (xs == 0 ? 0 : cdf[xs - 1]))/cdf[15]);
}
/*Estimates the cost of encoding a value with a given CDF.*/
double od_encode_cdf_cost(int val, uint16_t *cdf, int n) {
int total_prob;
int prev_prob;
double val_prob;
OD_ASSERT(n > 0);
total_prob = cdf[n - 1];
if (val == 0) {
prev_prob = 0;
}
else {
prev_prob = cdf[val - 1];
}
val_prob = (cdf[val] - prev_prob) / (double)total_prob;
return -OD_LOG2(val_prob);
}