1 // Copyright 2012 Google Inc. All Rights Reserved.
2 //
3 // Use of this source code is governed by a BSD-style license
4 // that can be found in the COPYING file in the root of the source
5 // tree. An additional intellectual property rights grant can be found
6 // in the file PATENTS. All contributing project authors may
7 // be found in the AUTHORS file in the root of the source tree.
8 // -----------------------------------------------------------------------------
9 //
10 // Author: Jyrki Alakuijala (jyrki@google.com)
11 //
12 #ifdef HAVE_CONFIG_H
13 #include "config.h"
14 #endif
15
16 #include <math.h>
17 #include <stdio.h>
18
19 #include "./backward_references.h"
20 #include "./histogram.h"
21 #include "../dsp/lossless.h"
22 #include "../utils/utils.h"
23
HistogramClear(VP8LHistogram * const p)24 static void HistogramClear(VP8LHistogram* const p) {
25 memset(p->literal_, 0, sizeof(p->literal_));
26 memset(p->red_, 0, sizeof(p->red_));
27 memset(p->blue_, 0, sizeof(p->blue_));
28 memset(p->alpha_, 0, sizeof(p->alpha_));
29 memset(p->distance_, 0, sizeof(p->distance_));
30 p->bit_cost_ = 0;
31 }
32
VP8LHistogramStoreRefs(const VP8LBackwardRefs * const refs,VP8LHistogram * const histo)33 void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs,
34 VP8LHistogram* const histo) {
35 int i;
36 for (i = 0; i < refs->size; ++i) {
37 VP8LHistogramAddSinglePixOrCopy(histo, &refs->refs[i]);
38 }
39 }
40
VP8LHistogramCreate(VP8LHistogram * const p,const VP8LBackwardRefs * const refs,int palette_code_bits)41 void VP8LHistogramCreate(VP8LHistogram* const p,
42 const VP8LBackwardRefs* const refs,
43 int palette_code_bits) {
44 if (palette_code_bits >= 0) {
45 p->palette_code_bits_ = palette_code_bits;
46 }
47 HistogramClear(p);
48 VP8LHistogramStoreRefs(refs, p);
49 }
50
VP8LHistogramInit(VP8LHistogram * const p,int palette_code_bits)51 void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) {
52 p->palette_code_bits_ = palette_code_bits;
53 HistogramClear(p);
54 }
55
VP8LAllocateHistogramSet(int size,int cache_bits)56 VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
57 int i;
58 VP8LHistogramSet* set;
59 VP8LHistogram* bulk;
60 const uint64_t total_size = sizeof(*set)
61 + (uint64_t)size * sizeof(*set->histograms)
62 + (uint64_t)size * sizeof(**set->histograms);
63 uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
64 if (memory == NULL) return NULL;
65
66 set = (VP8LHistogramSet*)memory;
67 memory += sizeof(*set);
68 set->histograms = (VP8LHistogram**)memory;
69 memory += size * sizeof(*set->histograms);
70 bulk = (VP8LHistogram*)memory;
71 set->max_size = size;
72 set->size = size;
73 for (i = 0; i < size; ++i) {
74 set->histograms[i] = bulk + i;
75 VP8LHistogramInit(set->histograms[i], cache_bits);
76 }
77 return set;
78 }
79
80 // -----------------------------------------------------------------------------
81
VP8LHistogramAddSinglePixOrCopy(VP8LHistogram * const histo,const PixOrCopy * const v)82 void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
83 const PixOrCopy* const v) {
84 if (PixOrCopyIsLiteral(v)) {
85 ++histo->alpha_[PixOrCopyLiteral(v, 3)];
86 ++histo->red_[PixOrCopyLiteral(v, 2)];
87 ++histo->literal_[PixOrCopyLiteral(v, 1)];
88 ++histo->blue_[PixOrCopyLiteral(v, 0)];
89 } else if (PixOrCopyIsCacheIdx(v)) {
90 int literal_ix = 256 + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
91 ++histo->literal_[literal_ix];
92 } else {
93 int code, extra_bits_count, extra_bits_value;
94 PrefixEncode(PixOrCopyLength(v),
95 &code, &extra_bits_count, &extra_bits_value);
96 ++histo->literal_[256 + code];
97 PrefixEncode(PixOrCopyDistance(v),
98 &code, &extra_bits_count, &extra_bits_value);
99 ++histo->distance_[code];
100 }
101 }
102
BitsEntropy(const int * const array,int n)103 static double BitsEntropy(const int* const array, int n) {
104 double retval = 0.;
105 int sum = 0;
106 int nonzeros = 0;
107 int max_val = 0;
108 int i;
109 double mix;
110 for (i = 0; i < n; ++i) {
111 if (array[i] != 0) {
112 sum += array[i];
113 ++nonzeros;
114 retval -= VP8LFastSLog2(array[i]);
115 if (max_val < array[i]) {
116 max_val = array[i];
117 }
118 }
119 }
120 retval += VP8LFastSLog2(sum);
121
122 if (nonzeros < 5) {
123 if (nonzeros <= 1) {
124 return 0;
125 }
126 // Two symbols, they will be 0 and 1 in a Huffman code.
127 // Let's mix in a bit of entropy to favor good clustering when
128 // distributions of these are combined.
129 if (nonzeros == 2) {
130 return 0.99 * sum + 0.01 * retval;
131 }
132 // No matter what the entropy says, we cannot be better than min_limit
133 // with Huffman coding. I am mixing a bit of entropy into the
134 // min_limit since it produces much better (~0.5 %) compression results
135 // perhaps because of better entropy clustering.
136 if (nonzeros == 3) {
137 mix = 0.95;
138 } else {
139 mix = 0.7; // nonzeros == 4.
140 }
141 } else {
142 mix = 0.627;
143 }
144
145 {
146 double min_limit = 2 * sum - max_val;
147 min_limit = mix * min_limit + (1.0 - mix) * retval;
148 return (retval < min_limit) ? min_limit : retval;
149 }
150 }
151
152 // Returns the cost encode the rle-encoded entropy code.
153 // The constants in this function are experimental.
HuffmanCost(const int * const population,int length)154 static double HuffmanCost(const int* const population, int length) {
155 // Small bias because Huffman code length is typically not stored in
156 // full length.
157 static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
158 static const double kSmallBias = 9.1;
159 double retval = kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
160 int streak = 0;
161 int i = 0;
162 for (; i < length - 1; ++i) {
163 ++streak;
164 if (population[i] == population[i + 1]) {
165 continue;
166 }
167 last_streak_hack:
168 // population[i] points now to the symbol in the streak of same values.
169 if (streak > 3) {
170 if (population[i] == 0) {
171 retval += 1.5625 + 0.234375 * streak;
172 } else {
173 retval += 2.578125 + 0.703125 * streak;
174 }
175 } else {
176 if (population[i] == 0) {
177 retval += 1.796875 * streak;
178 } else {
179 retval += 3.28125 * streak;
180 }
181 }
182 streak = 0;
183 }
184 if (i == length - 1) {
185 ++streak;
186 goto last_streak_hack;
187 }
188 return retval;
189 }
190
PopulationCost(const int * const population,int length)191 static double PopulationCost(const int* const population, int length) {
192 return BitsEntropy(population, length) + HuffmanCost(population, length);
193 }
194
ExtraCost(const int * const population,int length)195 static double ExtraCost(const int* const population, int length) {
196 int i;
197 double cost = 0.;
198 for (i = 2; i < length - 2; ++i) cost += (i >> 1) * population[i + 2];
199 return cost;
200 }
201
202 // Estimates the Entropy + Huffman + other block overhead size cost.
VP8LHistogramEstimateBits(const VP8LHistogram * const p)203 double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
204 return PopulationCost(p->literal_, VP8LHistogramNumCodes(p))
205 + PopulationCost(p->red_, 256)
206 + PopulationCost(p->blue_, 256)
207 + PopulationCost(p->alpha_, 256)
208 + PopulationCost(p->distance_, NUM_DISTANCE_CODES)
209 + ExtraCost(p->literal_ + 256, NUM_LENGTH_CODES)
210 + ExtraCost(p->distance_, NUM_DISTANCE_CODES);
211 }
212
VP8LHistogramEstimateBitsBulk(const VP8LHistogram * const p)213 double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) {
214 return BitsEntropy(p->literal_, VP8LHistogramNumCodes(p))
215 + BitsEntropy(p->red_, 256)
216 + BitsEntropy(p->blue_, 256)
217 + BitsEntropy(p->alpha_, 256)
218 + BitsEntropy(p->distance_, NUM_DISTANCE_CODES)
219 + ExtraCost(p->literal_ + 256, NUM_LENGTH_CODES)
220 + ExtraCost(p->distance_, NUM_DISTANCE_CODES);
221 }
222
223 // -----------------------------------------------------------------------------
224 // Various histogram combine/cost-eval functions
225
226 // Adds 'in' histogram to 'out'
HistogramAdd(const VP8LHistogram * const in,VP8LHistogram * const out)227 static void HistogramAdd(const VP8LHistogram* const in,
228 VP8LHistogram* const out) {
229 int i;
230 for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
231 out->literal_[i] += in->literal_[i];
232 }
233 for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
234 out->distance_[i] += in->distance_[i];
235 }
236 for (i = 0; i < 256; ++i) {
237 out->red_[i] += in->red_[i];
238 out->blue_[i] += in->blue_[i];
239 out->alpha_[i] += in->alpha_[i];
240 }
241 }
242
243 // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
244 // to the threshold value 'cost_threshold'. The score returned is
245 // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
246 // Since the previous score passed is 'cost_threshold', we only need to compare
247 // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out
248 // early.
HistogramAddEval(const VP8LHistogram * const a,const VP8LHistogram * const b,VP8LHistogram * const out,double cost_threshold)249 static double HistogramAddEval(const VP8LHistogram* const a,
250 const VP8LHistogram* const b,
251 VP8LHistogram* const out,
252 double cost_threshold) {
253 double cost = 0;
254 const double sum_cost = a->bit_cost_ + b->bit_cost_;
255 int i;
256
257 cost_threshold += sum_cost;
258
259 // palette_code_bits_ is part of the cost evaluation for literal_.
260 // TODO(skal): remove/simplify this palette_code_bits_?
261 out->palette_code_bits_ =
262 (a->palette_code_bits_ > b->palette_code_bits_) ? a->palette_code_bits_ :
263 b->palette_code_bits_;
264 for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
265 out->literal_[i] = a->literal_[i] + b->literal_[i];
266 }
267 cost += PopulationCost(out->literal_, VP8LHistogramNumCodes(out));
268 cost += ExtraCost(out->literal_ + 256, NUM_LENGTH_CODES);
269 if (cost > cost_threshold) return cost;
270
271 for (i = 0; i < 256; ++i) out->red_[i] = a->red_[i] + b->red_[i];
272 cost += PopulationCost(out->red_, 256);
273 if (cost > cost_threshold) return cost;
274
275 for (i = 0; i < 256; ++i) out->blue_[i] = a->blue_[i] + b->blue_[i];
276 cost += PopulationCost(out->blue_, 256);
277 if (cost > cost_threshold) return cost;
278
279 for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
280 out->distance_[i] = a->distance_[i] + b->distance_[i];
281 }
282 cost += PopulationCost(out->distance_, NUM_DISTANCE_CODES);
283 cost += ExtraCost(out->distance_, NUM_DISTANCE_CODES);
284 if (cost > cost_threshold) return cost;
285
286 for (i = 0; i < 256; ++i) out->alpha_[i] = a->alpha_[i] + b->alpha_[i];
287 cost += PopulationCost(out->alpha_, 256);
288
289 out->bit_cost_ = cost;
290 return cost - sum_cost;
291 }
292
293 // Same as HistogramAddEval(), except that the resulting histogram
294 // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit
295 // the term C(b) which is constant over all the evaluations.
HistogramAddThresh(const VP8LHistogram * const a,const VP8LHistogram * const b,double cost_threshold)296 static double HistogramAddThresh(const VP8LHistogram* const a,
297 const VP8LHistogram* const b,
298 double cost_threshold) {
299 int tmp[PIX_OR_COPY_CODES_MAX]; // <= max storage we'll need
300 int i;
301 double cost = -a->bit_cost_;
302
303 for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
304 tmp[i] = a->literal_[i] + b->literal_[i];
305 }
306 // note that the tests are ordered so that the usually largest
307 // cost shares come first.
308 cost += PopulationCost(tmp, VP8LHistogramNumCodes(a));
309 cost += ExtraCost(tmp + 256, NUM_LENGTH_CODES);
310 if (cost > cost_threshold) return cost;
311
312 for (i = 0; i < 256; ++i) tmp[i] = a->red_[i] + b->red_[i];
313 cost += PopulationCost(tmp, 256);
314 if (cost > cost_threshold) return cost;
315
316 for (i = 0; i < 256; ++i) tmp[i] = a->blue_[i] + b->blue_[i];
317 cost += PopulationCost(tmp, 256);
318 if (cost > cost_threshold) return cost;
319
320 for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
321 tmp[i] = a->distance_[i] + b->distance_[i];
322 }
323 cost += PopulationCost(tmp, NUM_DISTANCE_CODES);
324 cost += ExtraCost(tmp, NUM_DISTANCE_CODES);
325 if (cost > cost_threshold) return cost;
326
327 for (i = 0; i < 256; ++i) tmp[i] = a->alpha_[i] + b->alpha_[i];
328 cost += PopulationCost(tmp, 256);
329
330 return cost;
331 }
332
333 // -----------------------------------------------------------------------------
334
HistogramBuildImage(int xsize,int histo_bits,const VP8LBackwardRefs * const backward_refs,VP8LHistogramSet * const image)335 static void HistogramBuildImage(int xsize, int histo_bits,
336 const VP8LBackwardRefs* const backward_refs,
337 VP8LHistogramSet* const image) {
338 int i;
339 int x = 0, y = 0;
340 const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
341 VP8LHistogram** const histograms = image->histograms;
342 assert(histo_bits > 0);
343 for (i = 0; i < backward_refs->size; ++i) {
344 const PixOrCopy* const v = &backward_refs->refs[i];
345 const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
346 VP8LHistogramAddSinglePixOrCopy(histograms[ix], v);
347 x += PixOrCopyLength(v);
348 while (x >= xsize) {
349 x -= xsize;
350 ++y;
351 }
352 }
353 }
354
MyRand(uint32_t * seed)355 static uint32_t MyRand(uint32_t *seed) {
356 *seed *= 16807U;
357 if (*seed == 0) {
358 *seed = 1;
359 }
360 return *seed;
361 }
362
HistogramCombine(const VP8LHistogramSet * const in,VP8LHistogramSet * const out,int iter_mult,int num_pairs,int num_tries_no_success)363 static int HistogramCombine(const VP8LHistogramSet* const in,
364 VP8LHistogramSet* const out, int iter_mult,
365 int num_pairs, int num_tries_no_success) {
366 int ok = 0;
367 int i, iter;
368 uint32_t seed = 0;
369 int tries_with_no_success = 0;
370 int out_size = in->size;
371 const int outer_iters = in->size * iter_mult;
372 const int min_cluster_size = 2;
373 VP8LHistogram* const histos = (VP8LHistogram*)malloc(2 * sizeof(*histos));
374 VP8LHistogram* cur_combo = histos + 0; // trial merged histogram
375 VP8LHistogram* best_combo = histos + 1; // best merged histogram so far
376 if (histos == NULL) goto End;
377
378 // Copy histograms from in[] to out[].
379 assert(in->size <= out->size);
380 for (i = 0; i < in->size; ++i) {
381 in->histograms[i]->bit_cost_ = VP8LHistogramEstimateBits(in->histograms[i]);
382 *out->histograms[i] = *in->histograms[i];
383 }
384
385 // Collapse similar histograms in 'out'.
386 for (iter = 0; iter < outer_iters && out_size >= min_cluster_size; ++iter) {
387 double best_cost_diff = 0.;
388 int best_idx1 = -1, best_idx2 = 1;
389 int j;
390 const int num_tries = (num_pairs < out_size) ? num_pairs : out_size;
391 seed += iter;
392 for (j = 0; j < num_tries; ++j) {
393 double curr_cost_diff;
394 // Choose two histograms at random and try to combine them.
395 const uint32_t idx1 = MyRand(&seed) % out_size;
396 const uint32_t tmp = (j & 7) + 1;
397 const uint32_t diff = (tmp < 3) ? tmp : MyRand(&seed) % (out_size - 1);
398 const uint32_t idx2 = (idx1 + diff + 1) % out_size;
399 if (idx1 == idx2) {
400 continue;
401 }
402 // Calculate cost reduction on combining.
403 curr_cost_diff = HistogramAddEval(out->histograms[idx1],
404 out->histograms[idx2],
405 cur_combo, best_cost_diff);
406 if (curr_cost_diff < best_cost_diff) { // found a better pair?
407 { // swap cur/best combo histograms
408 VP8LHistogram* const tmp_histo = cur_combo;
409 cur_combo = best_combo;
410 best_combo = tmp_histo;
411 }
412 best_cost_diff = curr_cost_diff;
413 best_idx1 = idx1;
414 best_idx2 = idx2;
415 }
416 }
417
418 if (best_idx1 >= 0) {
419 *out->histograms[best_idx1] = *best_combo;
420 // swap best_idx2 slot with last one (which is now unused)
421 --out_size;
422 if (best_idx2 != out_size) {
423 out->histograms[best_idx2] = out->histograms[out_size];
424 out->histograms[out_size] = NULL; // just for sanity check.
425 }
426 tries_with_no_success = 0;
427 }
428 if (++tries_with_no_success >= num_tries_no_success) {
429 break;
430 }
431 }
432 out->size = out_size;
433 ok = 1;
434
435 End:
436 free(histos);
437 return ok;
438 }
439
440 // -----------------------------------------------------------------------------
441 // Histogram refinement
442
443 // What is the bit cost of moving square_histogram from cur_symbol to candidate.
HistogramDistance(const VP8LHistogram * const square_histogram,const VP8LHistogram * const candidate,double cost_threshold)444 static double HistogramDistance(const VP8LHistogram* const square_histogram,
445 const VP8LHistogram* const candidate,
446 double cost_threshold) {
447 return HistogramAddThresh(candidate, square_histogram, cost_threshold);
448 }
449
450 // Find the best 'out' histogram for each of the 'in' histograms.
451 // Note: we assume that out[]->bit_cost_ is already up-to-date.
HistogramRemap(const VP8LHistogramSet * const in,const VP8LHistogramSet * const out,uint16_t * const symbols)452 static void HistogramRemap(const VP8LHistogramSet* const in,
453 const VP8LHistogramSet* const out,
454 uint16_t* const symbols) {
455 int i;
456 for (i = 0; i < in->size; ++i) {
457 int best_out = 0;
458 double best_bits =
459 HistogramDistance(in->histograms[i], out->histograms[0], 1.e38);
460 int k;
461 for (k = 1; k < out->size; ++k) {
462 const double cur_bits =
463 HistogramDistance(in->histograms[i], out->histograms[k], best_bits);
464 if (cur_bits < best_bits) {
465 best_bits = cur_bits;
466 best_out = k;
467 }
468 }
469 symbols[i] = best_out;
470 }
471
472 // Recompute each out based on raw and symbols.
473 for (i = 0; i < out->size; ++i) {
474 HistogramClear(out->histograms[i]);
475 }
476 for (i = 0; i < in->size; ++i) {
477 HistogramAdd(in->histograms[i], out->histograms[symbols[i]]);
478 }
479 }
480
VP8LGetHistoImageSymbols(int xsize,int ysize,const VP8LBackwardRefs * const refs,int quality,int histo_bits,int cache_bits,VP8LHistogramSet * const image_in,uint16_t * const histogram_symbols)481 int VP8LGetHistoImageSymbols(int xsize, int ysize,
482 const VP8LBackwardRefs* const refs,
483 int quality, int histo_bits, int cache_bits,
484 VP8LHistogramSet* const image_in,
485 uint16_t* const histogram_symbols) {
486 int ok = 0;
487 const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1;
488 const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1;
489 const int histo_image_raw_size = histo_xsize * histo_ysize;
490
491 // Heuristic params for HistogramCombine().
492 const int num_tries_no_success = 8 + (quality >> 1);
493 const int iter_mult = (quality < 27) ? 1 : 1 + ((quality - 27) >> 4);
494 const int num_pairs = (quality < 25) ? 10 : (5 * quality) >> 3;
495
496 VP8LHistogramSet* const image_out =
497 VP8LAllocateHistogramSet(histo_image_raw_size, cache_bits);
498 if (image_out == NULL) return 0;
499
500 // Build histogram image.
501 HistogramBuildImage(xsize, histo_bits, refs, image_out);
502 // Collapse similar histograms.
503 if (!HistogramCombine(image_out, image_in, iter_mult, num_pairs,
504 num_tries_no_success)) {
505 goto Error;
506 }
507 // Find the optimal map from original histograms to the final ones.
508 HistogramRemap(image_out, image_in, histogram_symbols);
509 ok = 1;
510
511 Error:
512 free(image_out);
513 return ok;
514 }
515