Update libwebp to 0.6.1

* lossless performance and compression improvements + a new 'cruncher' mode (-m 6 -q 100)
* ARM performance improvements with clang (15-20% w/ndk r15c)
* webp-js: emscripten/webassembly based javascript decoder
* miscellaneous bug & build fixes

1 files changed, 0 insertions, 750 deletions

diff --git a/thirdparty/libwebp/enc/predictor_enc.c b/thirdparty/libwebp/enc/predictor_enc.c
deleted file mode 100644
index 0639b74f1c..0000000000
--- a/thirdparty/libwebp/enc/predictor_enc.c
+++ /dev/null
@@ -1,750 +0,0 @@
-// Copyright 2016 Google Inc. All Rights Reserved.
-//
-// Use of this source code is governed by a BSD-style license
-// that can be found in the COPYING file in the root of the source
-// tree. An additional intellectual property rights grant can be found
-// in the file PATENTS. All contributing project authors may
-// be found in the AUTHORS file in the root of the source tree.
-// -----------------------------------------------------------------------------
-//
-// Image transform methods for lossless encoder.
-//
-// Authors: Vikas Arora (vikaas.arora@gmail.com)
-//          Jyrki Alakuijala (jyrki@google.com)
-//          Urvang Joshi (urvang@google.com)
-//          Vincent Rabaud (vrabaud@google.com)
-
-#include "../dsp/lossless.h"
-#include "../dsp/lossless_common.h"
-#include "./vp8li_enc.h"
-
-#define MAX_DIFF_COST (1e30f)
-
-static const float kSpatialPredictorBias = 15.f;
-static const int kPredLowEffort = 11;
-static const uint32_t kMaskAlpha = 0xff000000;
-
-// Mostly used to reduce code size + readability
-static WEBP_INLINE int GetMin(int a, int b) { return (a > b) ? b : a; }
-static WEBP_INLINE int GetMax(int a, int b) { return (a < b) ? b : a; }
-
-//------------------------------------------------------------------------------
-// Methods to calculate Entropy (Shannon).
-
-static float PredictionCostSpatial(const int counts[256], int weight_0,
-                                   double exp_val) {
-  const int significant_symbols = 256 >> 4;
-  const double exp_decay_factor = 0.6;
-  double bits = weight_0 * counts[0];
-  int i;
-  for (i = 1; i < significant_symbols; ++i) {
-    bits += exp_val * (counts[i] + counts[256 - i]);
-    exp_val *= exp_decay_factor;
-  }
-  return (float)(-0.1 * bits);
-}
-
-static float PredictionCostSpatialHistogram(const int accumulated[4][256],
-                                            const int tile[4][256]) {
-  int i;
-  double retval = 0;
-  for (i = 0; i < 4; ++i) {
-    const double kExpValue = 0.94;
-    retval += PredictionCostSpatial(tile[i], 1, kExpValue);
-    retval += VP8LCombinedShannonEntropy(tile[i], accumulated[i]);
-  }
-  return (float)retval;
-}
-
-static WEBP_INLINE void UpdateHisto(int histo_argb[4][256], uint32_t argb) {
-  ++histo_argb[0][argb >> 24];
-  ++histo_argb[1][(argb >> 16) & 0xff];
-  ++histo_argb[2][(argb >> 8) & 0xff];
-  ++histo_argb[3][argb & 0xff];
-}
-
-//------------------------------------------------------------------------------
-// Spatial transform functions.
-
-static WEBP_INLINE void PredictBatch(int mode, int x_start, int y,
-                                     int num_pixels, const uint32_t* current,
-                                     const uint32_t* upper, uint32_t* out) {
-  if (x_start == 0) {
-    if (y == 0) {
-      // ARGB_BLACK.
-      VP8LPredictorsSub[0](current, NULL, 1, out);
-    } else {
-      // Top one.
-      VP8LPredictorsSub[2](current, upper, 1, out);
-    }
-    ++x_start;
-    ++out;
-    --num_pixels;
-  }
-  if (y == 0) {
-    // Left one.
-    VP8LPredictorsSub[1](current + x_start, NULL, num_pixels, out);
-  } else {
-    VP8LPredictorsSub[mode](current + x_start, upper + x_start, num_pixels,
-                            out);
-  }
-}
-
-static int MaxDiffBetweenPixels(uint32_t p1, uint32_t p2) {
-  const int diff_a = abs((int)(p1 >> 24) - (int)(p2 >> 24));
-  const int diff_r = abs((int)((p1 >> 16) & 0xff) - (int)((p2 >> 16) & 0xff));
-  const int diff_g = abs((int)((p1 >> 8) & 0xff) - (int)((p2 >> 8) & 0xff));
-  const int diff_b = abs((int)(p1 & 0xff) - (int)(p2 & 0xff));
-  return GetMax(GetMax(diff_a, diff_r), GetMax(diff_g, diff_b));
-}
-
-static int MaxDiffAroundPixel(uint32_t current, uint32_t up, uint32_t down,
-                              uint32_t left, uint32_t right) {
-  const int diff_up = MaxDiffBetweenPixels(current, up);
-  const int diff_down = MaxDiffBetweenPixels(current, down);
-  const int diff_left = MaxDiffBetweenPixels(current, left);
-  const int diff_right = MaxDiffBetweenPixels(current, right);
-  return GetMax(GetMax(diff_up, diff_down), GetMax(diff_left, diff_right));
-}
-
-static uint32_t AddGreenToBlueAndRed(uint32_t argb) {
-  const uint32_t green = (argb >> 8) & 0xff;
-  uint32_t red_blue = argb & 0x00ff00ffu;
-  red_blue += (green << 16) | green;
-  red_blue &= 0x00ff00ffu;
-  return (argb & 0xff00ff00u) | red_blue;
-}
-
-static void MaxDiffsForRow(int width, int stride, const uint32_t* const argb,
-                           uint8_t* const max_diffs, int used_subtract_green) {
-  uint32_t current, up, down, left, right;
-  int x;
-  if (width <= 2) return;
-  current = argb[0];
-  right = argb[1];
-  if (used_subtract_green) {
-    current = AddGreenToBlueAndRed(current);
-    right = AddGreenToBlueAndRed(right);
-  }
-  // max_diffs[0] and max_diffs[width - 1] are never used.
-  for (x = 1; x < width - 1; ++x) {
-    up = argb[-stride + x];
-    down = argb[stride + x];
-    left = current;
-    current = right;
-    right = argb[x + 1];
-    if (used_subtract_green) {
-      up = AddGreenToBlueAndRed(up);
-      down = AddGreenToBlueAndRed(down);
-      right = AddGreenToBlueAndRed(right);
-    }
-    max_diffs[x] = MaxDiffAroundPixel(current, up, down, left, right);
-  }
-}
-
-// Quantize the difference between the actual component value and its prediction
-// to a multiple of quantization, working modulo 256, taking care not to cross
-// a boundary (inclusive upper limit).
-static uint8_t NearLosslessComponent(uint8_t value, uint8_t predict,
-                                     uint8_t boundary, int quantization) {
-  const int residual = (value - predict) & 0xff;
-  const int boundary_residual = (boundary - predict) & 0xff;
-  const int lower = residual & ~(quantization - 1);
-  const int upper = lower + quantization;
-  // Resolve ties towards a value closer to the prediction (i.e. towards lower
-  // if value comes after prediction and towards upper otherwise).
-  const int bias = ((boundary - value) & 0xff) < boundary_residual;
-  if (residual - lower < upper - residual + bias) {
-    // lower is closer to residual than upper.
-    if (residual > boundary_residual && lower <= boundary_residual) {
-      // Halve quantization step to avoid crossing boundary. This midpoint is
-      // on the same side of boundary as residual because midpoint >= residual
-      // (since lower is closer than upper) and residual is above the boundary.
-      return lower + (quantization >> 1);
-    }
-    return lower;
-  } else {
-    // upper is closer to residual than lower.
-    if (residual <= boundary_residual && upper > boundary_residual) {
-      // Halve quantization step to avoid crossing boundary. This midpoint is
-      // on the same side of boundary as residual because midpoint <= residual
-      // (since upper is closer than lower) and residual is below the boundary.
-      return lower + (quantization >> 1);
-    }
-    return upper & 0xff;
-  }
-}
-
-// Quantize every component of the difference between the actual pixel value and
-// its prediction to a multiple of a quantization (a power of 2, not larger than
-// max_quantization which is a power of 2, smaller than max_diff). Take care if
-// value and predict have undergone subtract green, which means that red and
-// blue are represented as offsets from green.
-static uint32_t NearLossless(uint32_t value, uint32_t predict,
-                             int max_quantization, int max_diff,
-                             int used_subtract_green) {
-  int quantization;
-  uint8_t new_green = 0;
-  uint8_t green_diff = 0;
-  uint8_t a, r, g, b;
-  if (max_diff <= 2) {
-    return VP8LSubPixels(value, predict);
-  }
-  quantization = max_quantization;
-  while (quantization >= max_diff) {
-    quantization >>= 1;
-  }
-  if ((value >> 24) == 0 || (value >> 24) == 0xff) {
-    // Preserve transparency of fully transparent or fully opaque pixels.
-    a = ((value >> 24) - (predict >> 24)) & 0xff;
-  } else {
-    a = NearLosslessComponent(value >> 24, predict >> 24, 0xff, quantization);
-  }
-  g = NearLosslessComponent((value >> 8) & 0xff, (predict >> 8) & 0xff, 0xff,
-                            quantization);
-  if (used_subtract_green) {
-    // The green offset will be added to red and blue components during decoding
-    // to obtain the actual red and blue values.
-    new_green = ((predict >> 8) + g) & 0xff;
-    // The amount by which green has been adjusted during quantization. It is
-    // subtracted from red and blue for compensation, to avoid accumulating two
-    // quantization errors in them.
-    green_diff = (new_green - (value >> 8)) & 0xff;
-  }
-  r = NearLosslessComponent(((value >> 16) - green_diff) & 0xff,
-                            (predict >> 16) & 0xff, 0xff - new_green,
-                            quantization);
-  b = NearLosslessComponent((value - green_diff) & 0xff, predict & 0xff,
-                            0xff - new_green, quantization);
-  return ((uint32_t)a << 24) | ((uint32_t)r << 16) | ((uint32_t)g << 8) | b;
-}
-
-// Stores the difference between the pixel and its prediction in "out".
-// In case of a lossy encoding, updates the source image to avoid propagating
-// the deviation further to pixels which depend on the current pixel for their
-// predictions.
-static WEBP_INLINE void GetResidual(
-    int width, int height, uint32_t* const upper_row,
-    uint32_t* const current_row, const uint8_t* const max_diffs, int mode,
-    int x_start, int x_end, int y, int max_quantization, int exact,
-    int used_subtract_green, uint32_t* const out) {
-  if (exact) {
-    PredictBatch(mode, x_start, y, x_end - x_start, current_row, upper_row,
-                 out);
-  } else {
-    const VP8LPredictorFunc pred_func = VP8LPredictors[mode];
-    int x;
-    for (x = x_start; x < x_end; ++x) {
-      uint32_t predict;
-      uint32_t residual;
-      if (y == 0) {
-        predict = (x == 0) ? ARGB_BLACK : current_row[x - 1];  // Left.
-      } else if (x == 0) {
-        predict = upper_row[x];  // Top.
-      } else {
-        predict = pred_func(current_row[x - 1], upper_row + x);
-      }
-      if (max_quantization == 1 || mode == 0 || y == 0 || y == height - 1 ||
-          x == 0 || x == width - 1) {
-        residual = VP8LSubPixels(current_row[x], predict);
-      } else {
-        residual = NearLossless(current_row[x], predict, max_quantization,
-                                max_diffs[x], used_subtract_green);
-        // Update the source image.
-        current_row[x] = VP8LAddPixels(predict, residual);
-        // x is never 0 here so we do not need to update upper_row like below.
-      }
-      if ((current_row[x] & kMaskAlpha) == 0) {
-        // If alpha is 0, cleanup RGB. We can choose the RGB values of the
-        // residual for best compression. The prediction of alpha itself can be
-        // non-zero and must be kept though. We choose RGB of the residual to be
-        // 0.
-        residual &= kMaskAlpha;
-        // Update the source image.
-        current_row[x] = predict & ~kMaskAlpha;
-        // The prediction for the rightmost pixel in a row uses the leftmost
-        // pixel
-        // in that row as its top-right context pixel. Hence if we change the
-        // leftmost pixel of current_row, the corresponding change must be
-        // applied
-        // to upper_row as well where top-right context is being read from.
-        if (x == 0 && y != 0) upper_row[width] = current_row[0];
-      }
-      out[x - x_start] = residual;
-    }
-  }
-}
-
-// Returns best predictor and updates the accumulated histogram.
-// If max_quantization > 1, assumes that near lossless processing will be
-// applied, quantizing residuals to multiples of quantization levels up to
-// max_quantization (the actual quantization level depends on smoothness near
-// the given pixel).
-static int GetBestPredictorForTile(int width, int height,
-                                   int tile_x, int tile_y, int bits,
-                                   int accumulated[4][256],
-                                   uint32_t* const argb_scratch,
-                                   const uint32_t* const argb,
-                                   int max_quantization,
-                                   int exact, int used_subtract_green,
-                                   const uint32_t* const modes) {
-  const int kNumPredModes = 14;
-  const int start_x = tile_x << bits;
-  const int start_y = tile_y << bits;
-  const int tile_size = 1 << bits;
-  const int max_y = GetMin(tile_size, height - start_y);
-  const int max_x = GetMin(tile_size, width - start_x);
-  // Whether there exist columns just outside the tile.
-  const int have_left = (start_x > 0);
-  const int have_right = (max_x < width - start_x);
-  // Position and size of the strip covering the tile and adjacent columns if
-  // they exist.
-  const int context_start_x = start_x - have_left;
-  const int context_width = max_x + have_left + have_right;
-  const int tiles_per_row = VP8LSubSampleSize(width, bits);
-  // Prediction modes of the left and above neighbor tiles.
-  const int left_mode = (tile_x > 0) ?
-      (modes[tile_y * tiles_per_row + tile_x - 1] >> 8) & 0xff : 0xff;
-  const int above_mode = (tile_y > 0) ?
-      (modes[(tile_y - 1) * tiles_per_row + tile_x] >> 8) & 0xff : 0xff;
-  // The width of upper_row and current_row is one pixel larger than image width
-  // to allow the top right pixel to point to the leftmost pixel of the next row
-  // when at the right edge.
-  uint32_t* upper_row = argb_scratch;
-  uint32_t* current_row = upper_row + width + 1;
-  uint8_t* const max_diffs = (uint8_t*)(current_row + width + 1);
-  float best_diff = MAX_DIFF_COST;
-  int best_mode = 0;
-  int mode;
-  int histo_stack_1[4][256];
-  int histo_stack_2[4][256];
-  // Need pointers to be able to swap arrays.
-  int (*histo_argb)[256] = histo_stack_1;
-  int (*best_histo)[256] = histo_stack_2;
-  int i, j;
-  uint32_t residuals[1 << MAX_TRANSFORM_BITS];
-  assert(bits <= MAX_TRANSFORM_BITS);
-  assert(max_x <= (1 << MAX_TRANSFORM_BITS));
-
-  for (mode = 0; mode < kNumPredModes; ++mode) {
-    float cur_diff;
-    int relative_y;
-    memset(histo_argb, 0, sizeof(histo_stack_1));
-    if (start_y > 0) {
-      // Read the row above the tile which will become the first upper_row.
-      // Include a pixel to the left if it exists; include a pixel to the right
-      // in all cases (wrapping to the leftmost pixel of the next row if it does
-      // not exist).
-      memcpy(current_row + context_start_x,
-             argb + (start_y - 1) * width + context_start_x,
-             sizeof(*argb) * (max_x + have_left + 1));
-    }
-    for (relative_y = 0; relative_y < max_y; ++relative_y) {
-      const int y = start_y + relative_y;
-      int relative_x;
-      uint32_t* tmp = upper_row;
-      upper_row = current_row;
-      current_row = tmp;
-      // Read current_row. Include a pixel to the left if it exists; include a
-      // pixel to the right in all cases except at the bottom right corner of
-      // the image (wrapping to the leftmost pixel of the next row if it does
-      // not exist in the current row).
-      memcpy(current_row + context_start_x,
-             argb + y * width + context_start_x,
-             sizeof(*argb) * (max_x + have_left + (y + 1 < height)));
-      if (max_quantization > 1 && y >= 1 && y + 1 < height) {
-        MaxDiffsForRow(context_width, width, argb + y * width + context_start_x,
-                       max_diffs + context_start_x, used_subtract_green);
-      }
-
-      GetResidual(width, height, upper_row, current_row, max_diffs, mode,
-                  start_x, start_x + max_x, y, max_quantization, exact,
-                  used_subtract_green, residuals);
-      for (relative_x = 0; relative_x < max_x; ++relative_x) {
-        UpdateHisto(histo_argb, residuals[relative_x]);
-      }
-    }
-    cur_diff = PredictionCostSpatialHistogram(
-        (const int (*)[256])accumulated, (const int (*)[256])histo_argb);
-    // Favor keeping the areas locally similar.
-    if (mode == left_mode) cur_diff -= kSpatialPredictorBias;
-    if (mode == above_mode) cur_diff -= kSpatialPredictorBias;
-
-    if (cur_diff < best_diff) {
-      int (*tmp)[256] = histo_argb;
-      histo_argb = best_histo;
-      best_histo = tmp;
-      best_diff = cur_diff;
-      best_mode = mode;
-    }
-  }
-
-  for (i = 0; i < 4; i++) {
-    for (j = 0; j < 256; j++) {
-      accumulated[i][j] += best_histo[i][j];
-    }
-  }
-
-  return best_mode;
-}
-
-// Converts pixels of the image to residuals with respect to predictions.
-// If max_quantization > 1, applies near lossless processing, quantizing
-// residuals to multiples of quantization levels up to max_quantization
-// (the actual quantization level depends on smoothness near the given pixel).
-static void CopyImageWithPrediction(int width, int height,
-                                    int bits, uint32_t* const modes,
-                                    uint32_t* const argb_scratch,
-                                    uint32_t* const argb,
-                                    int low_effort, int max_quantization,
-                                    int exact, int used_subtract_green) {
-  const int tiles_per_row = VP8LSubSampleSize(width, bits);
-  // The width of upper_row and current_row is one pixel larger than image width
-  // to allow the top right pixel to point to the leftmost pixel of the next row
-  // when at the right edge.
-  uint32_t* upper_row = argb_scratch;
-  uint32_t* current_row = upper_row + width + 1;
-  uint8_t* current_max_diffs = (uint8_t*)(current_row + width + 1);
-  uint8_t* lower_max_diffs = current_max_diffs + width;
-  int y;
-
-  for (y = 0; y < height; ++y) {
-    int x;
-    uint32_t* const tmp32 = upper_row;
-    upper_row = current_row;
-    current_row = tmp32;
-    memcpy(current_row, argb + y * width,
-           sizeof(*argb) * (width + (y + 1 < height)));
-
-    if (low_effort) {
-      PredictBatch(kPredLowEffort, 0, y, width, current_row, upper_row,
-                   argb + y * width);
-    } else {
-      if (max_quantization > 1) {
-        // Compute max_diffs for the lower row now, because that needs the
-        // contents of argb for the current row, which we will overwrite with
-        // residuals before proceeding with the next row.
-        uint8_t* const tmp8 = current_max_diffs;
-        current_max_diffs = lower_max_diffs;
-        lower_max_diffs = tmp8;
-        if (y + 2 < height) {
-          MaxDiffsForRow(width, width, argb + (y + 1) * width, lower_max_diffs,
-                         used_subtract_green);
-        }
-      }
-      for (x = 0; x < width;) {
-        const int mode =
-            (modes[(y >> bits) * tiles_per_row + (x >> bits)] >> 8) & 0xff;
-        int x_end = x + (1 << bits);
-        if (x_end > width) x_end = width;
-        GetResidual(width, height, upper_row, current_row, current_max_diffs,
-                    mode, x, x_end, y, max_quantization, exact,
-                    used_subtract_green, argb + y * width + x);
-        x = x_end;
-      }
-    }
-  }
-}
-
-// Finds the best predictor for each tile, and converts the image to residuals
-// with respect to predictions. If near_lossless_quality < 100, applies
-// near lossless processing, shaving off more bits of residuals for lower
-// qualities.
-void VP8LResidualImage(int width, int height, int bits, int low_effort,
-                       uint32_t* const argb, uint32_t* const argb_scratch,
-                       uint32_t* const image, int near_lossless_quality,
-                       int exact, int used_subtract_green) {
-  const int tiles_per_row = VP8LSubSampleSize(width, bits);
-  const int tiles_per_col = VP8LSubSampleSize(height, bits);
-  int tile_y;
-  int histo[4][256];
-  const int max_quantization = 1 << VP8LNearLosslessBits(near_lossless_quality);
-  if (low_effort) {
-    int i;
-    for (i = 0; i < tiles_per_row * tiles_per_col; ++i) {
-      image[i] = ARGB_BLACK | (kPredLowEffort << 8);
-    }
-  } else {
-    memset(histo, 0, sizeof(histo));
-    for (tile_y = 0; tile_y < tiles_per_col; ++tile_y) {
-      int tile_x;
-      for (tile_x = 0; tile_x < tiles_per_row; ++tile_x) {
-        const int pred = GetBestPredictorForTile(width, height, tile_x, tile_y,
-            bits, histo, argb_scratch, argb, max_quantization, exact,
-            used_subtract_green, image);
-        image[tile_y * tiles_per_row + tile_x] = ARGB_BLACK | (pred << 8);
-      }
-    }
-  }
-
-  CopyImageWithPrediction(width, height, bits, image, argb_scratch, argb,
-                          low_effort, max_quantization, exact,
-                          used_subtract_green);
-}
-
-//------------------------------------------------------------------------------
-// Color transform functions.
-
-static WEBP_INLINE void MultipliersClear(VP8LMultipliers* const m) {
-  m->green_to_red_ = 0;
-  m->green_to_blue_ = 0;
-  m->red_to_blue_ = 0;
-}
-
-static WEBP_INLINE void ColorCodeToMultipliers(uint32_t color_code,
-                                               VP8LMultipliers* const m) {
-  m->green_to_red_  = (color_code >>  0) & 0xff;
-  m->green_to_blue_ = (color_code >>  8) & 0xff;
-  m->red_to_blue_   = (color_code >> 16) & 0xff;
-}
-
-static WEBP_INLINE uint32_t MultipliersToColorCode(
-    const VP8LMultipliers* const m) {
-  return 0xff000000u |
-         ((uint32_t)(m->red_to_blue_) << 16) |
-         ((uint32_t)(m->green_to_blue_) << 8) |
-         m->green_to_red_;
-}
-
-static float PredictionCostCrossColor(const int accumulated[256],
-                                      const int counts[256]) {
-  // Favor low entropy, locally and globally.
-  // Favor small absolute values for PredictionCostSpatial
-  static const double kExpValue = 2.4;
-  return VP8LCombinedShannonEntropy(counts, accumulated) +
-         PredictionCostSpatial(counts, 3, kExpValue);
-}
-
-static float GetPredictionCostCrossColorRed(
-    const uint32_t* argb, int stride, int tile_width, int tile_height,
-    VP8LMultipliers prev_x, VP8LMultipliers prev_y, int green_to_red,
-    const int accumulated_red_histo[256]) {
-  int histo[256] = { 0 };
-  float cur_diff;
-
-  VP8LCollectColorRedTransforms(argb, stride, tile_width, tile_height,
-                                green_to_red, histo);
-
-  cur_diff = PredictionCostCrossColor(accumulated_red_histo, histo);
-  if ((uint8_t)green_to_red == prev_x.green_to_red_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if ((uint8_t)green_to_red == prev_y.green_to_red_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if (green_to_red == 0) {
-    cur_diff -= 3;
-  }
-  return cur_diff;
-}
-
-static void GetBestGreenToRed(
-    const uint32_t* argb, int stride, int tile_width, int tile_height,
-    VP8LMultipliers prev_x, VP8LMultipliers prev_y, int quality,
-    const int accumulated_red_histo[256], VP8LMultipliers* const best_tx) {
-  const int kMaxIters = 4 + ((7 * quality) >> 8);  // in range [4..6]
-  int green_to_red_best = 0;
-  int iter, offset;
-  float best_diff = GetPredictionCostCrossColorRed(
-      argb, stride, tile_width, tile_height, prev_x, prev_y,
-      green_to_red_best, accumulated_red_histo);
-  for (iter = 0; iter < kMaxIters; ++iter) {
-    // ColorTransformDelta is a 3.5 bit fixed point, so 32 is equal to
-    // one in color computation. Having initial delta here as 1 is sufficient
-    // to explore the range of (-2, 2).
-    const int delta = 32 >> iter;
-    // Try a negative and a positive delta from the best known value.
-    for (offset = -delta; offset <= delta; offset += 2 * delta) {
-      const int green_to_red_cur = offset + green_to_red_best;
-      const float cur_diff = GetPredictionCostCrossColorRed(
-          argb, stride, tile_width, tile_height, prev_x, prev_y,
-          green_to_red_cur, accumulated_red_histo);
-      if (cur_diff < best_diff) {
-        best_diff = cur_diff;
-        green_to_red_best = green_to_red_cur;
-      }
-    }
-  }
-  best_tx->green_to_red_ = green_to_red_best;
-}
-
-static float GetPredictionCostCrossColorBlue(
-    const uint32_t* argb, int stride, int tile_width, int tile_height,
-    VP8LMultipliers prev_x, VP8LMultipliers prev_y,
-    int green_to_blue, int red_to_blue, const int accumulated_blue_histo[256]) {
-  int histo[256] = { 0 };
-  float cur_diff;
-
-  VP8LCollectColorBlueTransforms(argb, stride, tile_width, tile_height,
-                                 green_to_blue, red_to_blue, histo);
-
-  cur_diff = PredictionCostCrossColor(accumulated_blue_histo, histo);
-  if ((uint8_t)green_to_blue == prev_x.green_to_blue_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if ((uint8_t)green_to_blue == prev_y.green_to_blue_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if ((uint8_t)red_to_blue == prev_x.red_to_blue_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if ((uint8_t)red_to_blue == prev_y.red_to_blue_) {
-    cur_diff -= 3;  // favor keeping the areas locally similar
-  }
-  if (green_to_blue == 0) {
-    cur_diff -= 3;
-  }
-  if (red_to_blue == 0) {
-    cur_diff -= 3;
-  }
-  return cur_diff;
-}
-
-#define kGreenRedToBlueNumAxis 8
-#define kGreenRedToBlueMaxIters 7
-static void GetBestGreenRedToBlue(
-    const uint32_t* argb, int stride, int tile_width, int tile_height,
-    VP8LMultipliers prev_x, VP8LMultipliers prev_y, int quality,
-    const int accumulated_blue_histo[256],
-    VP8LMultipliers* const best_tx) {
-  const int8_t offset[kGreenRedToBlueNumAxis][2] =
-      {{0, -1}, {0, 1}, {-1, 0}, {1, 0}, {-1, -1}, {-1, 1}, {1, -1}, {1, 1}};
-  const int8_t delta_lut[kGreenRedToBlueMaxIters] = { 16, 16, 8, 4, 2, 2, 2 };
-  const int iters =
-      (quality < 25) ? 1 : (quality > 50) ? kGreenRedToBlueMaxIters : 4;
-  int green_to_blue_best = 0;
-  int red_to_blue_best = 0;
-  int iter;
-  // Initial value at origin:
-  float best_diff = GetPredictionCostCrossColorBlue(
-      argb, stride, tile_width, tile_height, prev_x, prev_y,
-      green_to_blue_best, red_to_blue_best, accumulated_blue_histo);
-  for (iter = 0; iter < iters; ++iter) {
-    const int delta = delta_lut[iter];
-    int axis;
-    for (axis = 0; axis < kGreenRedToBlueNumAxis; ++axis) {
-      const int green_to_blue_cur =
-          offset[axis][0] * delta + green_to_blue_best;
-      const int red_to_blue_cur = offset[axis][1] * delta + red_to_blue_best;
-      const float cur_diff = GetPredictionCostCrossColorBlue(
-          argb, stride, tile_width, tile_height, prev_x, prev_y,
-          green_to_blue_cur, red_to_blue_cur, accumulated_blue_histo);
-      if (cur_diff < best_diff) {
-        best_diff = cur_diff;
-        green_to_blue_best = green_to_blue_cur;
-        red_to_blue_best = red_to_blue_cur;
-      }
-      if (quality < 25 && iter == 4) {
-        // Only axis aligned diffs for lower quality.
-        break;  // next iter.
-      }
-    }
-    if (delta == 2 && green_to_blue_best == 0 && red_to_blue_best == 0) {
-      // Further iterations would not help.
-      break;  // out of iter-loop.
-    }
-  }
-  best_tx->green_to_blue_ = green_to_blue_best;
-  best_tx->red_to_blue_ = red_to_blue_best;
-}
-#undef kGreenRedToBlueMaxIters
-#undef kGreenRedToBlueNumAxis
-
-static VP8LMultipliers GetBestColorTransformForTile(
-    int tile_x, int tile_y, int bits,
-    VP8LMultipliers prev_x,
-    VP8LMultipliers prev_y,
-    int quality, int xsize, int ysize,
-    const int accumulated_red_histo[256],
-    const int accumulated_blue_histo[256],
-    const uint32_t* const argb) {
-  const int max_tile_size = 1 << bits;
-  const int tile_y_offset = tile_y * max_tile_size;
-  const int tile_x_offset = tile_x * max_tile_size;
-  const int all_x_max = GetMin(tile_x_offset + max_tile_size, xsize);
-  const int all_y_max = GetMin(tile_y_offset + max_tile_size, ysize);
-  const int tile_width = all_x_max - tile_x_offset;
-  const int tile_height = all_y_max - tile_y_offset;
-  const uint32_t* const tile_argb = argb + tile_y_offset * xsize
-                                  + tile_x_offset;
-  VP8LMultipliers best_tx;
-  MultipliersClear(&best_tx);
-
-  GetBestGreenToRed(tile_argb, xsize, tile_width, tile_height,
-                    prev_x, prev_y, quality, accumulated_red_histo, &best_tx);
-  GetBestGreenRedToBlue(tile_argb, xsize, tile_width, tile_height,
-                        prev_x, prev_y, quality, accumulated_blue_histo,
-                        &best_tx);
-  return best_tx;
-}
-
-static void CopyTileWithColorTransform(int xsize, int ysize,
-                                       int tile_x, int tile_y,
-                                       int max_tile_size,
-                                       VP8LMultipliers color_transform,
-                                       uint32_t* argb) {
-  const int xscan = GetMin(max_tile_size, xsize - tile_x);
-  int yscan = GetMin(max_tile_size, ysize - tile_y);
-  argb += tile_y * xsize + tile_x;
-  while (yscan-- > 0) {
-    VP8LTransformColor(&color_transform, argb, xscan);
-    argb += xsize;
-  }
-}
-
-void VP8LColorSpaceTransform(int width, int height, int bits, int quality,
-                             uint32_t* const argb, uint32_t* image) {
-  const int max_tile_size = 1 << bits;
-  const int tile_xsize = VP8LSubSampleSize(width, bits);
-  const int tile_ysize = VP8LSubSampleSize(height, bits);
-  int accumulated_red_histo[256] = { 0 };
-  int accumulated_blue_histo[256] = { 0 };
-  int tile_x, tile_y;
-  VP8LMultipliers prev_x, prev_y;
-  MultipliersClear(&prev_y);
-  MultipliersClear(&prev_x);
-  for (tile_y = 0; tile_y < tile_ysize; ++tile_y) {
-    for (tile_x = 0; tile_x < tile_xsize; ++tile_x) {
-      int y;
-      const int tile_x_offset = tile_x * max_tile_size;
-      const int tile_y_offset = tile_y * max_tile_size;
-      const int all_x_max = GetMin(tile_x_offset + max_tile_size, width);
-      const int all_y_max = GetMin(tile_y_offset + max_tile_size, height);
-      const int offset = tile_y * tile_xsize + tile_x;
-      if (tile_y != 0) {
-        ColorCodeToMultipliers(image[offset - tile_xsize], &prev_y);
-      }
-      prev_x = GetBestColorTransformForTile(tile_x, tile_y, bits,
-                                            prev_x, prev_y,
-                                            quality, width, height,
-                                            accumulated_red_histo,
-                                            accumulated_blue_histo,
-                                            argb);
-      image[offset] = MultipliersToColorCode(&prev_x);
-      CopyTileWithColorTransform(width, height, tile_x_offset, tile_y_offset,
-                                 max_tile_size, prev_x, argb);
-
-      // Gather accumulated histogram data.
-      for (y = tile_y_offset; y < all_y_max; ++y) {
-        int ix = y * width + tile_x_offset;
-        const int ix_end = ix + all_x_max - tile_x_offset;
-        for (; ix < ix_end; ++ix) {
-          const uint32_t pix = argb[ix];
-          if (ix >= 2 &&
-              pix == argb[ix - 2] &&
-              pix == argb[ix - 1]) {
-            continue;  // repeated pixels are handled by backward references
-          }
-          if (ix >= width + 2 &&
-              argb[ix - 2] == argb[ix - width - 2] &&
-              argb[ix - 1] == argb[ix - width - 1] &&
-              pix == argb[ix - width]) {
-            continue;  // repeated pixels are handled by backward references
-          }
-          ++accumulated_red_histo[(pix >> 16) & 0xff];
-          ++accumulated_blue_histo[(pix >> 0) & 0xff];
-        }
-      }
-    }
-  }
-}