1 /*
2 * Copyright (c) 2012 The WebM project authors. All Rights Reserved.
3 *
4 * Use of this source code is governed by a BSD-style license
5 * that can be found in the LICENSE file in the root of the source
6 * tree. An additional intellectual property rights grant can be found
7 * in the file PATENTS. All contributing project authors may
8 * be found in the AUTHORS file in the root of the source tree.
9 */
10
11 #include <limits.h>
12 #include <math.h>
13
14 #include "vpx_mem/vpx_mem.h"
15
16 #include "vp9/common/vp9_pred_common.h"
17 #include "vp9/common/vp9_tile_common.h"
18
19 #include "vp9/encoder/vp9_cost.h"
20 #include "vp9/encoder/vp9_segmentation.h"
21
vp9_enable_segmentation(struct segmentation * seg)22 void vp9_enable_segmentation(struct segmentation *seg) {
23 seg->enabled = 1;
24 seg->update_map = 1;
25 seg->update_data = 1;
26 }
27
vp9_disable_segmentation(struct segmentation * seg)28 void vp9_disable_segmentation(struct segmentation *seg) {
29 seg->enabled = 0;
30 seg->update_map = 0;
31 seg->update_data = 0;
32 }
33
vp9_set_segment_data(struct segmentation * seg,signed char * feature_data,unsigned char abs_delta)34 void vp9_set_segment_data(struct segmentation *seg, signed char *feature_data,
35 unsigned char abs_delta) {
36 seg->abs_delta = abs_delta;
37
38 memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
39 }
vp9_disable_segfeature(struct segmentation * seg,int segment_id,SEG_LVL_FEATURES feature_id)40 void vp9_disable_segfeature(struct segmentation *seg, int segment_id,
41 SEG_LVL_FEATURES feature_id) {
42 seg->feature_mask[segment_id] &= ~(1 << feature_id);
43 }
44
vp9_clear_segdata(struct segmentation * seg,int segment_id,SEG_LVL_FEATURES feature_id)45 void vp9_clear_segdata(struct segmentation *seg, int segment_id,
46 SEG_LVL_FEATURES feature_id) {
47 seg->feature_data[segment_id][feature_id] = 0;
48 }
49
vp9_psnr_aq_mode_setup(struct segmentation * seg)50 void vp9_psnr_aq_mode_setup(struct segmentation *seg) {
51 int i;
52
53 vp9_enable_segmentation(seg);
54 vp9_clearall_segfeatures(seg);
55 seg->abs_delta = SEGMENT_DELTADATA;
56
57 for (i = 0; i < MAX_SEGMENTS; ++i) {
58 vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 2 * (i - (MAX_SEGMENTS / 2)));
59 vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
60 }
61 }
62
vp9_perceptual_aq_mode_setup(struct VP9_COMP * cpi,struct segmentation * seg)63 void vp9_perceptual_aq_mode_setup(struct VP9_COMP *cpi,
64 struct segmentation *seg) {
65 const VP9_COMMON *cm = &cpi->common;
66 const int seg_counts = cpi->kmeans_ctr_num;
67 const int base_qindex = cm->base_qindex;
68 const double base_qstep = vp9_convert_qindex_to_q(base_qindex, cm->bit_depth);
69 const double mid_ctr = cpi->kmeans_ctr_ls[seg_counts / 2];
70 const double var_diff_scale = 4.0;
71 int i;
72
73 assert(seg_counts <= MAX_SEGMENTS);
74
75 vp9_enable_segmentation(seg);
76 vp9_clearall_segfeatures(seg);
77 seg->abs_delta = SEGMENT_DELTADATA;
78
79 for (i = 0; i < seg_counts / 2; ++i) {
80 double wiener_var_diff = mid_ctr - cpi->kmeans_ctr_ls[i];
81 double target_qstep = base_qstep / (1.0 + wiener_var_diff / var_diff_scale);
82 int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
83 assert(wiener_var_diff >= 0.0);
84
85 vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
86 vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
87 }
88
89 vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 0);
90 vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
91
92 for (; i < seg_counts; ++i) {
93 double wiener_var_diff = cpi->kmeans_ctr_ls[i] - mid_ctr;
94 double target_qstep = base_qstep * (1.0 + wiener_var_diff / var_diff_scale);
95 int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
96 assert(wiener_var_diff >= 0.0);
97
98 vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
99 vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
100 }
101 }
102
103 // Based on set of segment counts calculate a probability tree
calc_segtree_probs(int * segcounts,vpx_prob * segment_tree_probs)104 static void calc_segtree_probs(int *segcounts, vpx_prob *segment_tree_probs) {
105 // Work out probabilities of each segment
106 const int c01 = segcounts[0] + segcounts[1];
107 const int c23 = segcounts[2] + segcounts[3];
108 const int c45 = segcounts[4] + segcounts[5];
109 const int c67 = segcounts[6] + segcounts[7];
110
111 segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
112 segment_tree_probs[1] = get_binary_prob(c01, c23);
113 segment_tree_probs[2] = get_binary_prob(c45, c67);
114 segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
115 segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
116 segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
117 segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
118 }
119
120 // Based on set of segment counts and probabilities calculate a cost estimate
cost_segmap(int * segcounts,vpx_prob * probs)121 static int cost_segmap(int *segcounts, vpx_prob *probs) {
122 const int c01 = segcounts[0] + segcounts[1];
123 const int c23 = segcounts[2] + segcounts[3];
124 const int c45 = segcounts[4] + segcounts[5];
125 const int c67 = segcounts[6] + segcounts[7];
126 const int c0123 = c01 + c23;
127 const int c4567 = c45 + c67;
128
129 // Cost the top node of the tree
130 int cost = c0123 * vp9_cost_zero(probs[0]) + c4567 * vp9_cost_one(probs[0]);
131
132 // Cost subsequent levels
133 if (c0123 > 0) {
134 cost += c01 * vp9_cost_zero(probs[1]) + c23 * vp9_cost_one(probs[1]);
135
136 if (c01 > 0)
137 cost += segcounts[0] * vp9_cost_zero(probs[3]) +
138 segcounts[1] * vp9_cost_one(probs[3]);
139 if (c23 > 0)
140 cost += segcounts[2] * vp9_cost_zero(probs[4]) +
141 segcounts[3] * vp9_cost_one(probs[4]);
142 }
143
144 if (c4567 > 0) {
145 cost += c45 * vp9_cost_zero(probs[2]) + c67 * vp9_cost_one(probs[2]);
146
147 if (c45 > 0)
148 cost += segcounts[4] * vp9_cost_zero(probs[5]) +
149 segcounts[5] * vp9_cost_one(probs[5]);
150 if (c67 > 0)
151 cost += segcounts[6] * vp9_cost_zero(probs[6]) +
152 segcounts[7] * vp9_cost_one(probs[6]);
153 }
154
155 return cost;
156 }
157
count_segs(const VP9_COMMON * cm,MACROBLOCKD * xd,const TileInfo * tile,MODE_INFO ** mi,int * no_pred_segcounts,int (* temporal_predictor_count)[2],int * t_unpred_seg_counts,int bw,int bh,int mi_row,int mi_col)158 static void count_segs(const VP9_COMMON *cm, MACROBLOCKD *xd,
159 const TileInfo *tile, MODE_INFO **mi,
160 int *no_pred_segcounts,
161 int (*temporal_predictor_count)[2],
162 int *t_unpred_seg_counts, int bw, int bh, int mi_row,
163 int mi_col) {
164 int segment_id;
165
166 if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
167
168 xd->mi = mi;
169 segment_id = xd->mi[0]->segment_id;
170
171 set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw, cm->mi_rows, cm->mi_cols);
172
173 // Count the number of hits on each segment with no prediction
174 no_pred_segcounts[segment_id]++;
175
176 // Temporal prediction not allowed on key frames
177 if (cm->frame_type != KEY_FRAME) {
178 const BLOCK_SIZE bsize = xd->mi[0]->sb_type;
179 // Test to see if the segment id matches the predicted value.
180 const int pred_segment_id =
181 get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col);
182 const int pred_flag = pred_segment_id == segment_id;
183 const int pred_context = vp9_get_pred_context_seg_id(xd);
184
185 // Store the prediction status for this mb and update counts
186 // as appropriate
187 xd->mi[0]->seg_id_predicted = pred_flag;
188 temporal_predictor_count[pred_context][pred_flag]++;
189
190 // Update the "unpredicted" segment count
191 if (!pred_flag) t_unpred_seg_counts[segment_id]++;
192 }
193 }
194
count_segs_sb(const VP9_COMMON * cm,MACROBLOCKD * xd,const TileInfo * tile,MODE_INFO ** mi,int * no_pred_segcounts,int (* temporal_predictor_count)[2],int * t_unpred_seg_counts,int mi_row,int mi_col,BLOCK_SIZE bsize)195 static void count_segs_sb(const VP9_COMMON *cm, MACROBLOCKD *xd,
196 const TileInfo *tile, MODE_INFO **mi,
197 int *no_pred_segcounts,
198 int (*temporal_predictor_count)[2],
199 int *t_unpred_seg_counts, int mi_row, int mi_col,
200 BLOCK_SIZE bsize) {
201 const int mis = cm->mi_stride;
202 int bw, bh;
203 const int bs = num_8x8_blocks_wide_lookup[bsize], hbs = bs / 2;
204
205 if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
206
207 bw = num_8x8_blocks_wide_lookup[mi[0]->sb_type];
208 bh = num_8x8_blocks_high_lookup[mi[0]->sb_type];
209
210 if (bw == bs && bh == bs) {
211 count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
212 t_unpred_seg_counts, bs, bs, mi_row, mi_col);
213 } else if (bw == bs && bh < bs) {
214 count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
215 t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
216 count_segs(cm, xd, tile, mi + hbs * mis, no_pred_segcounts,
217 temporal_predictor_count, t_unpred_seg_counts, bs, hbs,
218 mi_row + hbs, mi_col);
219 } else if (bw < bs && bh == bs) {
220 count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
221 t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
222 count_segs(cm, xd, tile, mi + hbs, no_pred_segcounts,
223 temporal_predictor_count, t_unpred_seg_counts, hbs, bs, mi_row,
224 mi_col + hbs);
225 } else {
226 const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
227 int n;
228
229 assert(bw < bs && bh < bs);
230
231 for (n = 0; n < 4; n++) {
232 const int mi_dc = hbs * (n & 1);
233 const int mi_dr = hbs * (n >> 1);
234
235 count_segs_sb(cm, xd, tile, &mi[mi_dr * mis + mi_dc], no_pred_segcounts,
236 temporal_predictor_count, t_unpred_seg_counts,
237 mi_row + mi_dr, mi_col + mi_dc, subsize);
238 }
239 }
240 }
241
vp9_choose_segmap_coding_method(VP9_COMMON * cm,MACROBLOCKD * xd)242 void vp9_choose_segmap_coding_method(VP9_COMMON *cm, MACROBLOCKD *xd) {
243 struct segmentation *seg = &cm->seg;
244
245 int no_pred_cost;
246 int t_pred_cost = INT_MAX;
247
248 int i, tile_col, mi_row, mi_col;
249
250 int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } };
251 int no_pred_segcounts[MAX_SEGMENTS] = { 0 };
252 int t_unpred_seg_counts[MAX_SEGMENTS] = { 0 };
253
254 vpx_prob no_pred_tree[SEG_TREE_PROBS];
255 vpx_prob t_pred_tree[SEG_TREE_PROBS];
256 vpx_prob t_nopred_prob[PREDICTION_PROBS];
257
258 // Set default state for the segment tree probabilities and the
259 // temporal coding probabilities
260 memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
261 memset(seg->pred_probs, 255, sizeof(seg->pred_probs));
262
263 // First of all generate stats regarding how well the last segment map
264 // predicts this one
265 for (tile_col = 0; tile_col < 1 << cm->log2_tile_cols; tile_col++) {
266 TileInfo tile;
267 MODE_INFO **mi_ptr;
268 vp9_tile_init(&tile, cm, 0, tile_col);
269
270 mi_ptr = cm->mi_grid_visible + tile.mi_col_start;
271 for (mi_row = 0; mi_row < cm->mi_rows;
272 mi_row += 8, mi_ptr += 8 * cm->mi_stride) {
273 MODE_INFO **mi = mi_ptr;
274 for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
275 mi_col += 8, mi += 8)
276 count_segs_sb(cm, xd, &tile, mi, no_pred_segcounts,
277 temporal_predictor_count, t_unpred_seg_counts, mi_row,
278 mi_col, BLOCK_64X64);
279 }
280 }
281
282 // Work out probability tree for coding segments without prediction
283 // and the cost.
284 calc_segtree_probs(no_pred_segcounts, no_pred_tree);
285 no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
286
287 // Key frames cannot use temporal prediction
288 if (!frame_is_intra_only(cm)) {
289 // Work out probability tree for coding those segments not
290 // predicted using the temporal method and the cost.
291 calc_segtree_probs(t_unpred_seg_counts, t_pred_tree);
292 t_pred_cost = cost_segmap(t_unpred_seg_counts, t_pred_tree);
293
294 // Add in the cost of the signaling for each prediction context.
295 for (i = 0; i < PREDICTION_PROBS; i++) {
296 const int count0 = temporal_predictor_count[i][0];
297 const int count1 = temporal_predictor_count[i][1];
298
299 t_nopred_prob[i] = get_binary_prob(count0, count1);
300
301 // Add in the predictor signaling cost
302 t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) +
303 count1 * vp9_cost_one(t_nopred_prob[i]);
304 }
305 }
306
307 // Now choose which coding method to use.
308 if (t_pred_cost < no_pred_cost) {
309 seg->temporal_update = 1;
310 memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
311 memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
312 } else {
313 seg->temporal_update = 0;
314 memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
315 }
316 }
317
vp9_reset_segment_features(struct segmentation * seg)318 void vp9_reset_segment_features(struct segmentation *seg) {
319 // Set up default state for MB feature flags
320 seg->enabled = 0;
321 seg->update_map = 0;
322 seg->update_data = 0;
323 memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
324 vp9_clearall_segfeatures(seg);
325 }
326