/* * 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 "generic_code.h" void aom_cdf_init_q15_1D(uint16_t *cdf, int nsyms, int cdf_size) { int i; for (i = 0; i < nsyms; i++) cdf[i] = AOM_ICDF((i + 1)*CDF_PROB_TOP/nsyms); cdf[cdf_size - 1] = 0; } /** Adapts a Q15 cdf after encoding/decoding a symbol. */ void aom_cdf_adapt_q15(int val, uint16_t *cdf, int n, int *count, int rate) { int i; *count = OD_MINI(*count + 1, 1 << rate); OD_ASSERT(AOM_ICDF(cdf[n - 1]) == 32768); if (*count >= 1 << rate) { /* Steady-state adaptation based on a simple IIR with dyadic rate. */ for (i = 0; i < n; i++) { int tmp; /* When (i < val), we want the adjustment ((cdf[i] - tmp) >> rate) to be positive so long as (cdf[i] > i + 1), and 0 when (cdf[i] == i + 1), to ensure we don't drive any probabilities to 0. Replacing cdf[i] with (i + 2) and solving ((i + 2 - tmp) >> rate == 1) for tmp produces tmp == i + 2 - (1 << rate). Using this value of tmp with cdf[i] == i + 1 instead gives an adjustment of 0 as desired. When (i >= val), we want ((cdf[i] - tmp) >> rate) to be negative so long as cdf[i] < 32768 - (n - 1 - i), and 0 when cdf[i] == 32768 - (n - 1 - i), again to ensure we don't drive any probabilities to 0. Since right-shifting any negative value is still negative, we can solve (32768 - (n - 1 - i) - tmp == 0) for tmp, producing tmp = 32769 - n + i. Using this value of tmp with smaller values of cdf[i] instead gives negative adjustments, as desired. Combining the two cases gives the expression below. These could be stored in a lookup table indexed by n and rate to avoid the arithmetic. */ tmp = 2 - (1<= val); cdf[i] = AOM_ICDF(AOM_ICDF(cdf[i]) - ((AOM_ICDF(cdf[i]) - tmp) >> rate)); } } else { int alpha; /* Initial adaptation for the first symbols. The adaptation rate is computed to be equivalent to what od_{en,de}code_cdf_adapt() does when the initial cdf is set to increment/4. */ alpha = 4*32768/(n + 4**count); for (i = 0; i < n; i++) { int tmp; tmp = (32768 - n)*(i >= val) + i + 1; cdf[i] = AOM_ICDF(AOM_ICDF(cdf[i]) - (((AOM_ICDF(cdf[i]) - tmp)*alpha) >> 15)); } } OD_ASSERT(AOM_ICDF(cdf[n - 1]) == 32768); } /** Takes the base-2 log of E(x) in Q1. * * @param [in] ExQ16 expectation of x in Q16 * * @retval 2*log2(ExQ16/2^16) */ int log_ex(int ex_q16) { int lg; int lg_q1; int odd; lg = OD_ILOG(ex_q16); if (lg < 15) { odd = ex_q16*ex_q16 > 2 << 2*lg; } else { int tmp; tmp = ex_q16 >> (lg - 8); odd = tmp*tmp > (1 << 15); } lg_q1 = OD_MAXI(0, 2*lg - 33 + odd); return lg_q1; } /** Updates the probability model based on the encoded/decoded value * * @param [in,out] model generic prob model * @param [in,out] ExQ16 expectation of x * @param [in] x variable encoded/decoded (used for ExQ16) * @param [in] xs variable x after shift (used for the model) * @param [in] id id of the icdf to adapt * @param [in] integration integration period of ExQ16 (leaky average over * 1<