/* * Copyright (c) 2017, 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. */ #include #include #include #include #include "aom_dsp/noise_util.h" #include "aom_dsp/fft_common.h" #include "aom_mem/aom_mem.h" #include "config/aom_dsp_rtcd.h" float aom_noise_psd_get_default_value(int block_size, float factor) { return (factor * factor / 10000) * block_size * block_size / 8; } // Internal representation of noise transform. It keeps track of the // transformed data and a temporary working buffer to use during the // transform. struct aom_noise_tx_t { float *tx_block; float *temp; int block_size; void (*fft)(const float *, float *, float *); void (*ifft)(const float *, float *, float *); }; struct aom_noise_tx_t *aom_noise_tx_malloc(int block_size) { struct aom_noise_tx_t *noise_tx = (struct aom_noise_tx_t *)aom_malloc(sizeof(struct aom_noise_tx_t)); if (!noise_tx) return NULL; memset(noise_tx, 0, sizeof(*noise_tx)); switch (block_size) { case 2: noise_tx->fft = aom_fft2x2_float; noise_tx->ifft = aom_ifft2x2_float; break; case 4: noise_tx->fft = aom_fft4x4_float; noise_tx->ifft = aom_ifft4x4_float; break; case 8: noise_tx->fft = aom_fft8x8_float; noise_tx->ifft = aom_ifft8x8_float; break; case 16: noise_tx->fft = aom_fft16x16_float; noise_tx->ifft = aom_ifft16x16_float; break; case 32: noise_tx->fft = aom_fft32x32_float; noise_tx->ifft = aom_ifft32x32_float; break; default: aom_free(noise_tx); fprintf(stderr, "Unsupported block size %d\n", block_size); return NULL; } noise_tx->block_size = block_size; noise_tx->tx_block = (float *)aom_memalign( 32, 2 * sizeof(*noise_tx->tx_block) * block_size * block_size); noise_tx->temp = (float *)aom_memalign( 32, 2 * sizeof(*noise_tx->temp) * block_size * block_size); if (!noise_tx->tx_block || !noise_tx->temp) { aom_noise_tx_free(noise_tx); return NULL; } // Clear the buffers up front. Some outputs of the forward transform are // real only (the imaginary component will never be touched) memset(noise_tx->tx_block, 0, 2 * sizeof(*noise_tx->tx_block) * block_size * block_size); memset(noise_tx->temp, 0, 2 * sizeof(*noise_tx->temp) * block_size * block_size); return noise_tx; } void aom_noise_tx_forward(struct aom_noise_tx_t *noise_tx, const float *data) { noise_tx->fft(data, noise_tx->temp, noise_tx->tx_block); } void aom_noise_tx_filter(struct aom_noise_tx_t *noise_tx, const float *psd) { const int block_size = noise_tx->block_size; const float kBeta = 1.1f; const float kEps = 1e-6f; for (int y = 0; y < block_size; ++y) { for (int x = 0; x < block_size; ++x) { int i = y * block_size + x; float *c = noise_tx->tx_block + 2 * i; const float c0 = AOMMAX((float)fabs(c[0]), 1e-8f); const float c1 = AOMMAX((float)fabs(c[1]), 1e-8f); const float p = c0 * c0 + c1 * c1; if (p > kBeta * psd[i] && p > 1e-6) { noise_tx->tx_block[2 * i + 0] *= (p - psd[i]) / AOMMAX(p, kEps); noise_tx->tx_block[2 * i + 1] *= (p - psd[i]) / AOMMAX(p, kEps); } else { noise_tx->tx_block[2 * i + 0] *= (kBeta - 1.0f) / kBeta; noise_tx->tx_block[2 * i + 1] *= (kBeta - 1.0f) / kBeta; } } } } void aom_noise_tx_inverse(struct aom_noise_tx_t *noise_tx, float *data) { const int n = noise_tx->block_size * noise_tx->block_size; noise_tx->ifft(noise_tx->tx_block, noise_tx->temp, data); for (int i = 0; i < n; ++i) { data[i] /= n; } } void aom_noise_tx_add_energy(const struct aom_noise_tx_t *noise_tx, float *psd) { const int block_size = noise_tx->block_size; for (int yb = 0; yb < block_size; ++yb) { for (int xb = 0; xb <= block_size / 2; ++xb) { float *c = noise_tx->tx_block + 2 * (yb * block_size + xb); psd[yb * block_size + xb] += c[0] * c[0] + c[1] * c[1]; } } } void aom_noise_tx_free(struct aom_noise_tx_t *noise_tx) { if (!noise_tx) return; aom_free(noise_tx->tx_block); aom_free(noise_tx->temp); aom_free(noise_tx); } double aom_normalized_cross_correlation(const double *a, const double *b, int n) { double c = 0; double a_len = 0; double b_len = 0; for (int i = 0; i < n; ++i) { a_len += a[i] * a[i]; b_len += b[i] * b[i]; c += a[i] * b[i]; } return c / (sqrt(a_len) * sqrt(b_len)); } int aom_noise_data_validate(const double *data, int w, int h) { const double kVarianceThreshold = 2; const double kMeanThreshold = 2; int x = 0, y = 0; int ret_value = 1; double var = 0, mean = 0; double *mean_x, *mean_y, *var_x, *var_y; // Check that noise variance is not increasing in x or y // and that the data is zero mean. mean_x = (double *)aom_malloc(sizeof(*mean_x) * w); var_x = (double *)aom_malloc(sizeof(*var_x) * w); mean_y = (double *)aom_malloc(sizeof(*mean_x) * h); var_y = (double *)aom_malloc(sizeof(*var_y) * h); memset(mean_x, 0, sizeof(*mean_x) * w); memset(var_x, 0, sizeof(*var_x) * w); memset(mean_y, 0, sizeof(*mean_y) * h); memset(var_y, 0, sizeof(*var_y) * h); for (y = 0; y < h; ++y) { for (x = 0; x < w; ++x) { const double d = data[y * w + x]; var_x[x] += d * d; var_y[y] += d * d; mean_x[x] += d; mean_y[y] += d; var += d * d; mean += d; } } mean /= (w * h); var = var / (w * h) - mean * mean; for (y = 0; y < h; ++y) { mean_y[y] /= h; var_y[y] = var_y[y] / h - mean_y[y] * mean_y[y]; if (fabs(var_y[y] - var) >= kVarianceThreshold) { fprintf(stderr, "Variance distance too large %f %f\n", var_y[y], var); ret_value = 0; break; } if (fabs(mean_y[y] - mean) >= kMeanThreshold) { fprintf(stderr, "Mean distance too large %f %f\n", mean_y[y], mean); ret_value = 0; break; } } for (x = 0; x < w; ++x) { mean_x[x] /= w; var_x[x] = var_x[x] / w - mean_x[x] * mean_x[x]; if (fabs(var_x[x] - var) >= kVarianceThreshold) { fprintf(stderr, "Variance distance too large %f %f\n", var_x[x], var); ret_value = 0; break; } if (fabs(mean_x[x] - mean) >= kMeanThreshold) { fprintf(stderr, "Mean distance too large %f %f\n", mean_x[x], mean); ret_value = 0; break; } } aom_free(mean_x); aom_free(mean_y); aom_free(var_x); aom_free(var_y); return ret_value; }