114 строки
3.9 KiB
C
114 строки
3.9 KiB
C
/*
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* Copyright (c) 2001-2016, Alliance for Open Media. All rights reserved
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*
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* This source code is subject to the terms of the BSD 2 Clause License and
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* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
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* was not distributed with this source code in the LICENSE file, you can
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* obtain it at www.aomedia.org/license/software. If the Alliance for Open
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* Media Patent License 1.0 was not distributed with this source code in the
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* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
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*/
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/* clang-format off */
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#ifdef HAVE_CONFIG_H
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# include "config.h"
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#endif
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#include "generic_code.h"
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void aom_cdf_init_q15_1D(uint16_t *cdf, int nsyms, int cdf_size) {
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int i;
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for (i = 0; i < nsyms; i++)
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cdf[i] = (i + 1)*CDF_PROB_TOP/nsyms;
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#if CONFIG_EC_ADAPT
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cdf[cdf_size - 1] = 0;
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#endif
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}
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/** Adapts a Q15 cdf after encoding/decoding a symbol. */
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void aom_cdf_adapt_q15(int val, uint16_t *cdf, int n, int *count, int rate) {
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int i;
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*count = OD_MINI(*count + 1, 1 << rate);
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OD_ASSERT(cdf[n - 1] == 32768);
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if (*count >= 1 << rate) {
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/* Steady-state adaptation based on a simple IIR with dyadic rate. */
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for (i = 0; i < n; i++) {
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int tmp;
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/* When (i < val), we want the adjustment ((cdf[i] - tmp) >> rate) to be
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positive so long as (cdf[i] > i + 1), and 0 when (cdf[i] == i + 1),
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to ensure we don't drive any probabilities to 0. Replacing cdf[i] with
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(i + 2) and solving ((i + 2 - tmp) >> rate == 1) for tmp produces
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tmp == i + 2 - (1 << rate). Using this value of tmp with
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cdf[i] == i + 1 instead gives an adjustment of 0 as desired.
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When (i >= val), we want ((cdf[i] - tmp) >> rate) to be negative so
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long as cdf[i] < 32768 - (n - 1 - i), and 0 when
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cdf[i] == 32768 - (n - 1 - i), again to ensure we don't drive any
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probabilities to 0. Since right-shifting any negative value is still
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negative, we can solve (32768 - (n - 1 - i) - tmp == 0) for tmp,
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producing tmp = 32769 - n + i. Using this value of tmp with smaller
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values of cdf[i] instead gives negative adjustments, as desired.
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Combining the two cases gives the expression below. These could be
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stored in a lookup table indexed by n and rate to avoid the
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arithmetic. */
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tmp = 2 - (1<<rate) + i + (32767 + (1<<rate) - n)*(i >= val);
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cdf[i] -= (cdf[i] - tmp) >> rate;
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}
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}
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else {
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int alpha;
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/* Initial adaptation for the first symbols. The adaptation rate is
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computed to be equivalent to what od_{en,de}code_cdf_adapt() does
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when the initial cdf is set to increment/4. */
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alpha = 4*32768/(n + 4**count);
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for (i = 0; i < n; i++) {
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int tmp;
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tmp = (32768 - n)*(i >= val) + i + 1;
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cdf[i] -= ((cdf[i] - tmp)*alpha) >> 15;
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}
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}
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OD_ASSERT(cdf[n - 1] == 32768);
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}
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/** Takes the base-2 log of E(x) in Q1.
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*
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* @param [in] ExQ16 expectation of x in Q16
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*
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* @retval 2*log2(ExQ16/2^16)
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*/
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int log_ex(int ex_q16) {
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int lg;
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int lg_q1;
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int odd;
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lg = OD_ILOG(ex_q16);
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if (lg < 15) {
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odd = ex_q16*ex_q16 > 2 << 2*lg;
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}
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else {
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int tmp;
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tmp = ex_q16 >> (lg - 8);
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odd = tmp*tmp > (1 << 15);
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}
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lg_q1 = OD_MAXI(0, 2*lg - 33 + odd);
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return lg_q1;
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}
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/** Updates the probability model based on the encoded/decoded value
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*
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* @param [in,out] model generic prob model
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* @param [in,out] ExQ16 expectation of x
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* @param [in] x variable encoded/decoded (used for ExQ16)
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* @param [in] xs variable x after shift (used for the model)
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* @param [in] id id of the icdf to adapt
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* @param [in] integration integration period of ExQ16 (leaky average over
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* 1<<integration samples)
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*/
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void generic_model_update(int *ex_q16, int x, int integration) {
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/* We could have saturated ExQ16 directly, but this is safe and simpler */
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x = OD_MINI(x, 32767);
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OD_IIR_DIADIC(*ex_q16, x << 16, integration);
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}
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