mirror of
https://github.com/webmproject/libwebp.git
synced 2025-07-14 21:09:55 +02:00
new segmentation algorithm
fixes the 'blocky sky problem' (saturation problem: when luma was flat, chroma noise was taking over, resulting in random segment id assigned. When just using a common uniform segment was better). + side clean-up and readibility/experimentability MACRO'ization + added '-map 7' option Change-Id: I35982a9e43c0fecbfdd7b05e4813e8ba8c121d71
This commit is contained in:
@ -23,10 +23,6 @@ extern "C" {
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#define MAX_ITERS_K_MEANS 6
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static int ClipAlpha(int alpha) {
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return alpha < 0 ? 0 : alpha > 255 ? 255 : alpha;
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}
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//------------------------------------------------------------------------------
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// Smooth the segment map by replacing isolated block by the majority of its
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// neighbours.
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@ -115,7 +111,7 @@ static void SetSegmentProbas(VP8Encoder* const enc) {
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}
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static WEBP_INLINE int clip(int v, int m, int M) {
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return v < m ? m : v > M ? M : v;
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return (v < m) ? m : (v > M) ? M : v;
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}
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static void SetSegmentAlphas(VP8Encoder* const enc,
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@ -141,23 +137,64 @@ static void SetSegmentAlphas(VP8Encoder* const enc,
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}
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}
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//------------------------------------------------------------------------------
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// Compute susceptibility based on DCT-coeff histograms:
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// the higher, the "easier" the macroblock is to compress.
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#define MAX_ALPHA 255 // 8b of precision for susceptibilities.
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#define ALPHA_SCALE (2 * MAX_ALPHA) // scaling factor for alpha.
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#define DEFAULT_ALPHA (-1)
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#define IS_BETTER_ALPHA(alpha, best_alpha) ((alpha) > (best_alpha))
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static int FinalAlphaValue(int alpha) {
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alpha = MAX_ALPHA - alpha;
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return clip(alpha, 0, MAX_ALPHA);
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}
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static int GetAlpha(const VP8Histogram* const histo) {
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int max_value = 0, last_non_zero = 1;
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int k;
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int alpha;
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for (k = 0; k <= MAX_COEFF_THRESH; ++k) {
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const int value = histo->distribution[k];
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if (value > 0) {
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if (value > max_value) max_value = value;
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last_non_zero = k;
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}
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}
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// 'alpha' will later be clipped to [0..MAX_ALPHA] range, clamping outer
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// values which happen to be mostly noise. This leaves the maximum precision
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// for handling the useful small values which contribute most.
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alpha = (max_value > 1) ? ALPHA_SCALE * last_non_zero / max_value : 0;
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return alpha;
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}
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static void MergeHistograms(const VP8Histogram* const in,
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VP8Histogram* const out) {
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int i;
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for (i = 0; i <= MAX_COEFF_THRESH; ++i) {
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out->distribution[i] += in->distribution[i];
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}
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}
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//------------------------------------------------------------------------------
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// Simplified k-Means, to assign Nb segments based on alpha-histogram
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static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
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static void AssignSegments(VP8Encoder* const enc,
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const int alphas[MAX_ALPHA + 1]) {
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const int nb = enc->segment_hdr_.num_segments_;
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int centers[NUM_MB_SEGMENTS];
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int weighted_average = 0;
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int map[256];
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int map[MAX_ALPHA + 1];
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int a, n, k;
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int min_a = 0, max_a = 255, range_a;
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int min_a = 0, max_a = MAX_ALPHA, range_a;
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// 'int' type is ok for histo, and won't overflow
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int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS];
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// bracket the input
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for (n = 0; n < 256 && alphas[n] == 0; ++n) {}
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for (n = 0; n <= MAX_ALPHA && alphas[n] == 0; ++n) {}
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min_a = n;
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for (n = 255; n > min_a && alphas[n] == 0; --n) {}
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for (n = MAX_ALPHA; n > min_a && alphas[n] == 0; --n) {}
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max_a = n;
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range_a = max_a - min_a;
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@ -210,7 +247,7 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
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VP8MBInfo* const mb = &enc->mb_info_[n];
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const int alpha = mb->alpha_;
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mb->segment_ = map[alpha];
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mb->alpha_ = centers[map[alpha]]; // just for the record.
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mb->alpha_ = centers[map[alpha]]; // for the record.
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}
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if (nb > 1) {
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@ -236,15 +273,19 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
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static int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) {
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const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA16_MODE : 4;
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int mode;
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int best_alpha = -1;
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int best_alpha = DEFAULT_ALPHA;
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int best_mode = 0;
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VP8MakeLuma16Preds(it);
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for (mode = 0; mode < max_mode; ++mode) {
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const int alpha = VP8CollectHistogram(it->yuv_in_ + Y_OFF,
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it->yuv_p_ + VP8I16ModeOffsets[mode],
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0, 16);
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if (alpha > best_alpha) {
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VP8Histogram histo = { { 0 } };
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int alpha;
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VP8CollectHistogram(it->yuv_in_ + Y_OFF,
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it->yuv_p_ + VP8I16ModeOffsets[mode],
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0, 16, &histo);
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alpha = GetAlpha(&histo);
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if (IS_BETTER_ALPHA(alpha, best_alpha)) {
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best_alpha = alpha;
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best_mode = mode;
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}
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@ -257,45 +298,58 @@ static int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it,
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int best_alpha) {
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uint8_t modes[16];
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const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA4_MODE : NUM_BMODES;
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int i4_alpha = 0;
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int i4_alpha;
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VP8Histogram total_histo = { { 0 } };
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int cur_histo = 0;
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VP8IteratorStartI4(it);
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do {
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int mode;
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int best_mode_alpha = -1;
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int best_mode_alpha = DEFAULT_ALPHA;
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VP8Histogram histos[2];
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const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_];
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VP8MakeIntra4Preds(it);
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for (mode = 0; mode < max_mode; ++mode) {
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const int alpha = VP8CollectHistogram(src,
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it->yuv_p_ + VP8I4ModeOffsets[mode],
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0, 1);
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if (alpha > best_mode_alpha) {
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int alpha;
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memset(&histos[cur_histo], 0, sizeof(histos[cur_histo]));
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VP8CollectHistogram(src, it->yuv_p_ + VP8I4ModeOffsets[mode],
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0, 1, &histos[cur_histo]);
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alpha = GetAlpha(&histos[cur_histo]);
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if (IS_BETTER_ALPHA(alpha, best_mode_alpha)) {
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best_mode_alpha = alpha;
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modes[it->i4_] = mode;
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cur_histo ^= 1; // keep track of best histo so far.
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}
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}
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i4_alpha += best_mode_alpha;
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// accumulate best histogram
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MergeHistograms(&histos[cur_histo ^ 1], &total_histo);
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// Note: we reuse the original samples for predictors
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} while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF));
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if (i4_alpha > best_alpha) {
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i4_alpha = GetAlpha(&total_histo);
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if (IS_BETTER_ALPHA(i4_alpha, best_alpha)) {
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VP8SetIntra4Mode(it, modes);
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best_alpha = ClipAlpha(i4_alpha);
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best_alpha = i4_alpha;
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}
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return best_alpha;
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}
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static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
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int best_alpha = -1;
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int best_alpha = DEFAULT_ALPHA;
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int best_mode = 0;
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const int max_mode = (it->enc_->method_ >= 3) ? MAX_UV_MODE : 4;
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int mode;
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VP8MakeChroma8Preds(it);
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for (mode = 0; mode < max_mode; ++mode) {
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const int alpha = VP8CollectHistogram(it->yuv_in_ + U_OFF,
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it->yuv_p_ + VP8UVModeOffsets[mode],
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16, 16 + 4 + 4);
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if (alpha > best_alpha) {
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VP8Histogram histo = { { 0 } };
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int alpha;
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VP8CollectHistogram(it->yuv_in_ + U_OFF,
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it->yuv_p_ + VP8UVModeOffsets[mode],
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16, 16 + 4 + 4, &histo);
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alpha = GetAlpha(&histo);
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if (IS_BETTER_ALPHA(alpha, best_alpha)) {
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best_alpha = alpha;
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best_mode = mode;
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}
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@ -305,7 +359,7 @@ static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
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}
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static void MBAnalyze(VP8EncIterator* const it,
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int alphas[256], int* const uv_alpha) {
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int alphas[MAX_ALPHA + 1], int* const uv_alpha) {
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const VP8Encoder* const enc = it->enc_;
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int best_alpha, best_uv_alpha;
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@ -324,10 +378,11 @@ static void MBAnalyze(VP8EncIterator* const it,
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best_uv_alpha = MBAnalyzeBestUVMode(it);
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// Final susceptibility mix
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best_alpha = (best_alpha + best_uv_alpha + 1) / 2;
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best_alpha = (3 * best_alpha + best_uv_alpha + 2) >> 2;
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best_alpha = FinalAlphaValue(best_alpha);
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alphas[best_alpha]++;
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*uv_alpha += best_uv_alpha;
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it->mb_->alpha_ = best_alpha; // Informative only.
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it->mb_->alpha_ = best_alpha; // for later remapping.
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}
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//------------------------------------------------------------------------------
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@ -342,7 +397,7 @@ static void MBAnalyze(VP8EncIterator* const it,
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int VP8EncAnalyze(VP8Encoder* const enc) {
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int ok = 1;
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int alphas[256] = { 0 };
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int alphas[MAX_ALPHA + 1] = { 0 };
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VP8EncIterator it;
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VP8IteratorInit(enc, &it);
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@ -736,6 +736,7 @@ static void StoreSideInfo(const VP8EncIterator* const it) {
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const int b = (int)((it->luma_bits_ + it->uv_bits_ + 7) >> 3);
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*info = (b > 255) ? 255 : b; break;
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}
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case 7: *info = mb->alpha_; break;
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default: *info = 0; break;
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};
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}
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#define ENC_MIN_VERSION 2
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#define ENC_REV_VERSION 0
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// size of histogram used by CollectHistogram.
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#define MAX_COEFF_THRESH 64
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// intra prediction modes
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enum { B_DC_PRED = 0, // 4x4 modes
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B_TM_PRED = 1,
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@ -162,6 +159,14 @@ static WEBP_INLINE int QUANTDIV(int n, int iQ, int B) {
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}
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extern const uint8_t VP8Zigzag[16];
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// size of histogram used by CollectHistogram.
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#define MAX_COEFF_THRESH 31
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typedef struct VP8Histogram VP8Histogram;
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struct VP8Histogram {
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// TODO(skal): we only need to store the max_value and last_non_zero actually.
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int distribution[MAX_COEFF_THRESH + 1];
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};
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//------------------------------------------------------------------------------
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// Headers
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