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145 lines
4.0 KiB
145 lines
4.0 KiB
// Copyright 2011 Google Inc. All Rights Reserved. |
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// |
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// This code is licensed under the same terms as WebM: |
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// Software License Agreement: http://www.webmproject.org/license/software/ |
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// Additional IP Rights Grant: http://www.webmproject.org/license/additional/ |
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// ----------------------------------------------------------------------------- |
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// |
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// Quantize levels for specified number of quantization-levels ([2, 256]). |
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// Min and max values are preserved (usual 0 and 255 for alpha plane). |
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// |
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// Author: Skal (pascal.massimino@gmail.com) |
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#include <assert.h> |
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#include "./quant_levels.h" |
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#if defined(__cplusplus) || defined(c_plusplus) |
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extern "C" { |
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#endif |
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#define NUM_SYMBOLS 256 |
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#define MAX_ITER 6 // Maximum number of convergence steps. |
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#define ERROR_THRESHOLD 1e-4 // MSE stopping criterion. |
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// ----------------------------------------------------------------------------- |
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// Quantize levels. |
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int QuantizeLevels(uint8_t* const data, int width, int height, |
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int num_levels, uint64_t* const sse) { |
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int freq[NUM_SYMBOLS] = { 0 }; |
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int q_level[NUM_SYMBOLS] = { 0 }; |
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double inv_q_level[NUM_SYMBOLS] = { 0 }; |
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int min_s = 255, max_s = 0; |
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const size_t data_size = height * width; |
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int i, num_levels_in, iter; |
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double last_err = 1.e38, err = 0.; |
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const double err_threshold = ERROR_THRESHOLD * data_size; |
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if (data == NULL) { |
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return 0; |
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} |
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if (width <= 0 || height <= 0) { |
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return 0; |
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} |
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if (num_levels < 2 || num_levels > 256) { |
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return 0; |
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} |
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{ |
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size_t n; |
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num_levels_in = 0; |
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for (n = 0; n < data_size; ++n) { |
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num_levels_in += (freq[data[n]] == 0); |
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if (min_s > data[n]) min_s = data[n]; |
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if (max_s < data[n]) max_s = data[n]; |
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++freq[data[n]]; |
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} |
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} |
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if (num_levels_in <= num_levels) goto End; // nothing to do! |
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// Start with uniformly spread centroids. |
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for (i = 0; i < num_levels; ++i) { |
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inv_q_level[i] = min_s + (double)(max_s - min_s) * i / (num_levels - 1); |
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} |
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// Fixed values. Won't be changed. |
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q_level[min_s] = 0; |
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q_level[max_s] = num_levels - 1; |
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assert(inv_q_level[0] == min_s); |
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assert(inv_q_level[num_levels - 1] == max_s); |
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// k-Means iterations. |
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for (iter = 0; iter < MAX_ITER; ++iter) { |
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double q_sum[NUM_SYMBOLS] = { 0 }; |
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double q_count[NUM_SYMBOLS] = { 0 }; |
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int s, slot = 0; |
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// Assign classes to representatives. |
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for (s = min_s; s <= max_s; ++s) { |
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// Keep track of the nearest neighbour 'slot' |
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while (slot < num_levels - 1 && |
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2 * s > inv_q_level[slot] + inv_q_level[slot + 1]) { |
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++slot; |
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} |
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if (freq[s] > 0) { |
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q_sum[slot] += s * freq[s]; |
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q_count[slot] += freq[s]; |
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} |
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q_level[s] = slot; |
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} |
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// Assign new representatives to classes. |
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if (num_levels > 2) { |
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for (slot = 1; slot < num_levels - 1; ++slot) { |
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const double count = q_count[slot]; |
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if (count > 0.) { |
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inv_q_level[slot] = q_sum[slot] / count; |
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} |
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} |
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} |
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// Compute convergence error. |
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err = 0.; |
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for (s = min_s; s <= max_s; ++s) { |
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const double error = s - inv_q_level[q_level[s]]; |
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err += freq[s] * error * error; |
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} |
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// Check for convergence: we stop as soon as the error is no |
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// longer improving. |
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if (last_err - err < err_threshold) break; |
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last_err = err; |
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} |
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// Remap the alpha plane to quantized values. |
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{ |
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// double->int rounding operation can be costly, so we do it |
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// once for all before remapping. We also perform the data[] -> slot |
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// mapping, while at it (avoid one indirection in the final loop). |
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uint8_t map[NUM_SYMBOLS]; |
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int s; |
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size_t n; |
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for (s = min_s; s <= max_s; ++s) { |
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const int slot = q_level[s]; |
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map[s] = (uint8_t)(inv_q_level[slot] + .5); |
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} |
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// Final pass. |
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for (n = 0; n < data_size; ++n) { |
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data[n] = map[data[n]]; |
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} |
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} |
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End: |
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// Store sum of squared error if needed. |
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if (sse != NULL) *sse = (uint64_t)err; |
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return 1; |
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} |
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#if defined(__cplusplus) || defined(c_plusplus) |
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} // extern "C" |
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#endif
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