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      1 // Copyright 2011 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 // filter estimation
     11 //
     12 // Author: Urvang (urvang (at) google.com)
     13 
     14 #include "./filters_utils.h"
     15 #include <stdlib.h>
     16 #include <string.h>
     17 
     18 // -----------------------------------------------------------------------------
     19 // Quick estimate of a potentially interesting filter mode to try.
     20 
     21 #define SMAX 16
     22 #define SDIFF(a, b) (abs((a) - (b)) >> 4)   // Scoring diff, in [0..SMAX)
     23 
     24 static WEBP_INLINE int GradientPredictor(uint8_t a, uint8_t b, uint8_t c) {
     25   const int g = a + b - c;
     26   return ((g & ~0xff) == 0) ? g : (g < 0) ? 0 : 255;  // clip to 8bit
     27 }
     28 
     29 WEBP_FILTER_TYPE WebPEstimateBestFilter(const uint8_t* data,
     30                                         int width, int height, int stride) {
     31   int i, j;
     32   int bins[WEBP_FILTER_LAST][SMAX];
     33   memset(bins, 0, sizeof(bins));
     34 
     35   // We only sample every other pixels. That's enough.
     36   for (j = 2; j < height - 1; j += 2) {
     37     const uint8_t* const p = data + j * stride;
     38     int mean = p[0];
     39     for (i = 2; i < width - 1; i += 2) {
     40       const int diff0 = SDIFF(p[i], mean);
     41       const int diff1 = SDIFF(p[i], p[i - 1]);
     42       const int diff2 = SDIFF(p[i], p[i - width]);
     43       const int grad_pred =
     44           GradientPredictor(p[i - 1], p[i - width], p[i - width - 1]);
     45       const int diff3 = SDIFF(p[i], grad_pred);
     46       bins[WEBP_FILTER_NONE][diff0] = 1;
     47       bins[WEBP_FILTER_HORIZONTAL][diff1] = 1;
     48       bins[WEBP_FILTER_VERTICAL][diff2] = 1;
     49       bins[WEBP_FILTER_GRADIENT][diff3] = 1;
     50       mean = (3 * mean + p[i] + 2) >> 2;
     51     }
     52   }
     53   {
     54     int filter;
     55     WEBP_FILTER_TYPE best_filter = WEBP_FILTER_NONE;
     56     int best_score = 0x7fffffff;
     57     for (filter = WEBP_FILTER_NONE; filter < WEBP_FILTER_LAST; ++filter) {
     58       int score = 0;
     59       for (i = 0; i < SMAX; ++i) {
     60         if (bins[filter][i] > 0) {
     61           score += i;
     62         }
     63       }
     64       if (score < best_score) {
     65         best_score = score;
     66         best_filter = (WEBP_FILTER_TYPE)filter;
     67       }
     68     }
     69     return best_filter;
     70   }
     71 }
     72 
     73 #undef SMAX
     74 #undef SDIFF
     75 
     76 //------------------------------------------------------------------------------
     77