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Diffstat (limited to 'thirdparty/libwebp/src/utils/quant_levels_utils.c')
| -rw-r--r-- | thirdparty/libwebp/src/utils/quant_levels_utils.c | 140 |
1 files changed, 140 insertions, 0 deletions
diff --git a/thirdparty/libwebp/src/utils/quant_levels_utils.c b/thirdparty/libwebp/src/utils/quant_levels_utils.c new file mode 100644 index 0000000000..d65ad3c29d --- /dev/null +++ b/thirdparty/libwebp/src/utils/quant_levels_utils.c @@ -0,0 +1,140 @@ +// Copyright 2011 Google Inc. All Rights Reserved. +// +// Use of this source code is governed by a BSD-style license +// that can be found in the COPYING file in the root of the source +// tree. An additional intellectual property rights grant can be found +// in the file PATENTS. All contributing project authors may +// be found in the AUTHORS file in the root of the source tree. +// ----------------------------------------------------------------------------- +// +// Quantize levels for specified number of quantization-levels ([2, 256]). +// Min and max values are preserved (usual 0 and 255 for alpha plane). +// +// Author: Skal (pascal.massimino@gmail.com) + +#include <assert.h> + +#include "src/utils/quant_levels_utils.h" + +#define NUM_SYMBOLS 256 + +#define MAX_ITER 6 // Maximum number of convergence steps. +#define ERROR_THRESHOLD 1e-4 // MSE stopping criterion. + +// ----------------------------------------------------------------------------- +// Quantize levels. + +int QuantizeLevels(uint8_t* const data, int width, int height, + int num_levels, uint64_t* const sse) { + int freq[NUM_SYMBOLS] = { 0 }; + int q_level[NUM_SYMBOLS] = { 0 }; + double inv_q_level[NUM_SYMBOLS] = { 0 }; + int min_s = 255, max_s = 0; + const size_t data_size = height * width; + int i, num_levels_in, iter; + double last_err = 1.e38, err = 0.; + const double err_threshold = ERROR_THRESHOLD * data_size; + + if (data == NULL) { + return 0; + } + + if (width <= 0 || height <= 0) { + return 0; + } + + if (num_levels < 2 || num_levels > 256) { + return 0; + } + + { + size_t n; + num_levels_in = 0; + for (n = 0; n < data_size; ++n) { + num_levels_in += (freq[data[n]] == 0); + if (min_s > data[n]) min_s = data[n]; + if (max_s < data[n]) max_s = data[n]; + ++freq[data[n]]; + } + } + + if (num_levels_in <= num_levels) goto End; // nothing to do! + + // Start with uniformly spread centroids. + for (i = 0; i < num_levels; ++i) { + inv_q_level[i] = min_s + (double)(max_s - min_s) * i / (num_levels - 1); + } + + // Fixed values. Won't be changed. + q_level[min_s] = 0; + q_level[max_s] = num_levels - 1; + assert(inv_q_level[0] == min_s); + assert(inv_q_level[num_levels - 1] == max_s); + + // k-Means iterations. + for (iter = 0; iter < MAX_ITER; ++iter) { + double q_sum[NUM_SYMBOLS] = { 0 }; + double q_count[NUM_SYMBOLS] = { 0 }; + int s, slot = 0; + + // Assign classes to representatives. + for (s = min_s; s <= max_s; ++s) { + // Keep track of the nearest neighbour 'slot' + while (slot < num_levels - 1 && + 2 * s > inv_q_level[slot] + inv_q_level[slot + 1]) { + ++slot; + } + if (freq[s] > 0) { + q_sum[slot] += s * freq[s]; + q_count[slot] += freq[s]; + } + q_level[s] = slot; + } + + // Assign new representatives to classes. + if (num_levels > 2) { + for (slot = 1; slot < num_levels - 1; ++slot) { + const double count = q_count[slot]; + if (count > 0.) { + inv_q_level[slot] = q_sum[slot] / count; + } + } + } + + // Compute convergence error. + err = 0.; + for (s = min_s; s <= max_s; ++s) { + const double error = s - inv_q_level[q_level[s]]; + err += freq[s] * error * error; + } + + // Check for convergence: we stop as soon as the error is no + // longer improving. + if (last_err - err < err_threshold) break; + last_err = err; + } + + // Remap the alpha plane to quantized values. + { + // double->int rounding operation can be costly, so we do it + // once for all before remapping. We also perform the data[] -> slot + // mapping, while at it (avoid one indirection in the final loop). + uint8_t map[NUM_SYMBOLS]; + int s; + size_t n; + for (s = min_s; s <= max_s; ++s) { + const int slot = q_level[s]; + map[s] = (uint8_t)(inv_q_level[slot] + .5); + } + // Final pass. + for (n = 0; n < data_size; ++n) { + data[n] = map[data[n]]; + } + } + End: + // Store sum of squared error if needed. + if (sse != NULL) *sse = (uint64_t)err; + + return 1; +} + |