Roll skia to 8cc209111876b7c78b5ec577c9221d8ed5e21024

skia/ext/convolver.cc

Index: skia/ext/convolver.cc
diff --git a/skia/ext/convolver.cc b/skia/ext/convolver.cc
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+// Copyright (c) 2011 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include <algorithm>
+
+#include "base/logging.h"
+#include "skia/ext/convolver.h"
+#include "skia/ext/convolver_SSE2.h"
+#include "skia/ext/convolver_mips_dspr2.h"
+#include "third_party/skia/include/core/SkSize.h"
+#include "third_party/skia/include/core/SkTypes.h"
+
+namespace skia {
+
+namespace {
+
+// Converts the argument to an 8-bit unsigned value by clamping to the range
+// 0-255.
+inline unsigned char ClampTo8(int a) {
+  if (static_cast<unsigned>(a) < 256)
+    return a;  // Avoid the extra check in the common case.
+  if (a < 0)
+    return 0;
+  return 255;
+}
+
+// Takes the value produced by accumulating element-wise product of image with
+// a kernel and brings it back into range.
+// All of the filter scaling factors are in fixed point with kShiftBits bits of
+// fractional part.
+inline unsigned char BringBackTo8(int a, bool take_absolute) {
+  a >>= ConvolutionFilter1D::kShiftBits;
+  if (take_absolute)
+    a = std::abs(a);
+  return ClampTo8(a);
+}
+
+// Stores a list of rows in a circular buffer. The usage is you write into it
+// by calling AdvanceRow. It will keep track of which row in the buffer it
+// should use next, and the total number of rows added.
+class CircularRowBuffer {
+ public:
+  // The number of pixels in each row is given in |source_row_pixel_width|.
+  // The maximum number of rows needed in the buffer is |max_y_filter_size|
+  // (we only need to store enough rows for the biggest filter).
+  //
+  // We use the |first_input_row| to compute the coordinates of all of the
+  // following rows returned by Advance().
+  CircularRowBuffer(int dest_row_pixel_width,
+                    int max_y_filter_size,
+                    int first_input_row)
+      : row_byte_width_(dest_row_pixel_width * 4),
+        num_rows_(max_y_filter_size),
+        next_row_(0),
+        next_row_coordinate_(first_input_row) {
+    buffer_.resize(row_byte_width_ * max_y_filter_size);
+    row_addresses_.resize(num_rows_);
+  }
+
+  // Moves to the next row in the buffer, returning a pointer to the beginning
+  // of it.
+  unsigned char* AdvanceRow() {
+    unsigned char* row = &buffer_[next_row_ * row_byte_width_];
+    next_row_coordinate_++;
+
+    // Set the pointer to the next row to use, wrapping around if necessary.
+    next_row_++;
+    if (next_row_ == num_rows_)
+      next_row_ = 0;
+    return row;
+  }
+
+  // Returns a pointer to an "unrolled" array of rows. These rows will start
+  // at the y coordinate placed into |*first_row_index| and will continue in
+  // order for the maximum number of rows in this circular buffer.
+  //
+  // The |first_row_index_| may be negative. This means the circular buffer
+  // starts before the top of the image (it hasn't been filled yet).
+  unsigned char* const* GetRowAddresses(int* first_row_index) {
+    // Example for a 4-element circular buffer holding coords 6-9.
+    //   Row 0   Coord 8
+    //   Row 1   Coord 9
+    //   Row 2   Coord 6  <- next_row_ = 2, next_row_coordinate_ = 10.
+    //   Row 3   Coord 7
+    //
+    // The "next" row is also the first (lowest) coordinate. This computation
+    // may yield a negative value, but that's OK, the math will work out
+    // since the user of this buffer will compute the offset relative
+    // to the first_row_index and the negative rows will never be used.
+    *first_row_index = next_row_coordinate_ - num_rows_;
+
+    int cur_row = next_row_;
+    for (int i = 0; i < num_rows_; i++) {
+      row_addresses_[i] = &buffer_[cur_row * row_byte_width_];
+
+      // Advance to the next row, wrapping if necessary.
+      cur_row++;
+      if (cur_row == num_rows_)
+        cur_row = 0;
+    }
+    return &row_addresses_[0];
+  }
+
+ private:
+  // The buffer storing the rows. They are packed, each one row_byte_width_.
+  std::vector<unsigned char> buffer_;
+
+  // Number of bytes per row in the |buffer_|.
+  int row_byte_width_;
+
+  // The number of rows available in the buffer.
+  int num_rows_;
+
+  // The next row index we should write into. This wraps around as the
+  // circular buffer is used.
+  int next_row_;
+
+  // The y coordinate of the |next_row_|. This is incremented each time a
+  // new row is appended and does not wrap.
+  int next_row_coordinate_;
+
+  // Buffer used by GetRowAddresses().
+  std::vector<unsigned char*> row_addresses_;
+};
+
+// Convolves horizontally along a single row. The row data is given in
+// |src_data| and continues for the num_values() of the filter.
+template <bool has_alpha>
+void ConvolveHorizontally(const unsigned char* src_data,
+                          const ConvolutionFilter1D& filter,
+                          unsigned char* out_row) {
+  // Loop over each pixel on this row in the output image.
+  int num_values = filter.num_values();
+  for (int out_x = 0; out_x < num_values; out_x++) {
+    // Get the filter that determines the current output pixel.
+    int filter_offset, filter_length;
+    const ConvolutionFilter1D::Fixed* filter_values =
+        filter.FilterForValue(out_x, &filter_offset, &filter_length);
+
+    // Compute the first pixel in this row that the filter affects. It will
+    // touch |filter_length| pixels (4 bytes each) after this.
+    const unsigned char* row_to_filter = &src_data[filter_offset * 4];
+
+    // Apply the filter to the row to get the destination pixel in |accum|.
+    int accum[4] = {0};
+    for (int filter_x = 0; filter_x < filter_length; filter_x++) {
+      ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x];
+      accum[0] += cur_filter * row_to_filter[filter_x * 4 + 0];
+      accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1];
+      accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2];
+      if (has_alpha)
+        accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3];
+    }
+
+    // Bring this value back in range. All of the filter scaling factors
+    // are in fixed point with kShiftBits bits of fractional part.
+    accum[0] >>= ConvolutionFilter1D::kShiftBits;
+    accum[1] >>= ConvolutionFilter1D::kShiftBits;
+    accum[2] >>= ConvolutionFilter1D::kShiftBits;
+    if (has_alpha)
+      accum[3] >>= ConvolutionFilter1D::kShiftBits;
+
+    // Store the new pixel.
+    out_row[out_x * 4 + 0] = ClampTo8(accum[0]);
+    out_row[out_x * 4 + 1] = ClampTo8(accum[1]);
+    out_row[out_x * 4 + 2] = ClampTo8(accum[2]);
+    if (has_alpha)
+      out_row[out_x * 4 + 3] = ClampTo8(accum[3]);
+  }
+}
+
+// Does vertical convolution to produce one output row. The filter values and
+// length are given in the first two parameters. These are applied to each
+// of the rows pointed to in the |source_data_rows| array, with each row
+// being |pixel_width| wide.
+//
+// The output must have room for |pixel_width * 4| bytes.
+template <bool has_alpha>
+void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
+                        int filter_length,
+                        unsigned char* const* source_data_rows,
+                        int pixel_width,
+                        unsigned char* out_row) {
+  // We go through each column in the output and do a vertical convolution,
+  // generating one output pixel each time.
+  for (int out_x = 0; out_x < pixel_width; out_x++) {
+    // Compute the number of bytes over in each row that the current column
+    // we're convolving starts at. The pixel will cover the next 4 bytes.
+    int byte_offset = out_x * 4;
+
+    // Apply the filter to one column of pixels.
+    int accum[4] = {0};
+    for (int filter_y = 0; filter_y < filter_length; filter_y++) {
+      ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y];
+      accum[0] += cur_filter * source_data_rows[filter_y][byte_offset + 0];
+      accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1];
+      accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2];
+      if (has_alpha)
+        accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3];
+    }
+
+    // Bring this value back in range. All of the filter scaling factors
+    // are in fixed point with kShiftBits bits of precision.
+    accum[0] >>= ConvolutionFilter1D::kShiftBits;
+    accum[1] >>= ConvolutionFilter1D::kShiftBits;
+    accum[2] >>= ConvolutionFilter1D::kShiftBits;
+    if (has_alpha)
+      accum[3] >>= ConvolutionFilter1D::kShiftBits;
+
+    // Store the new pixel.
+    out_row[byte_offset + 0] = ClampTo8(accum[0]);
+    out_row[byte_offset + 1] = ClampTo8(accum[1]);
+    out_row[byte_offset + 2] = ClampTo8(accum[2]);
+    if (has_alpha) {
+      unsigned char alpha = ClampTo8(accum[3]);
+
+      // Make sure the alpha channel doesn't come out smaller than any of the
+      // color channels. We use premultipled alpha channels, so this should
+      // never happen, but rounding errors will cause this from time to time.
+      // These "impossible" colors will cause overflows (and hence random pixel
+      // values) when the resulting bitmap is drawn to the screen.
+      //
+      // We only need to do this when generating the final output row (here).
+      int max_color_channel = std::max(
+          out_row[byte_offset + 0],
+          std::max(out_row[byte_offset + 1], out_row[byte_offset + 2]));
+      if (alpha < max_color_channel)
+        out_row[byte_offset + 3] = max_color_channel;
+      else
+        out_row[byte_offset + 3] = alpha;
+    } else {
+      // No alpha channel, the image is opaque.
+      out_row[byte_offset + 3] = 0xff;
+    }
+  }
+}
+
+void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
+                        int filter_length,
+                        unsigned char* const* source_data_rows,
+                        int pixel_width,
+                        unsigned char* out_row,
+                        bool source_has_alpha) {
+  if (source_has_alpha) {
+    ConvolveVertically<true>(filter_values, filter_length, source_data_rows,
+                             pixel_width, out_row);
+  } else {
+    ConvolveVertically<false>(filter_values, filter_length, source_data_rows,
+                              pixel_width, out_row);
+  }
+}
+
+}  // namespace
+
+// ConvolutionFilter1D ---------------------------------------------------------
+
+ConvolutionFilter1D::ConvolutionFilter1D() : max_filter_(0) {}
+
+ConvolutionFilter1D::~ConvolutionFilter1D() {}
+
+void ConvolutionFilter1D::AddFilter(int filter_offset,
+                                    const float* filter_values,
+                                    int filter_length) {
+  SkASSERT(filter_length > 0);
+
+  std::vector<Fixed> fixed_values;
+  fixed_values.reserve(filter_length);
+
+  for (int i = 0; i < filter_length; ++i)
+    fixed_values.push_back(FloatToFixed(filter_values[i]));
+
+  AddFilter(filter_offset, &fixed_values[0], filter_length);
+}
+
+void ConvolutionFilter1D::AddFilter(int filter_offset,
+                                    const Fixed* filter_values,
+                                    int filter_length) {
+  // It is common for leading/trailing filter values to be zeros. In such
+  // cases it is beneficial to only store the central factors.
+  // For a scaling to 1/4th in each dimension using a Lanczos-2 filter on
+  // a 1080p image this optimization gives a ~10% speed improvement.
+  int filter_size = filter_length;
+  int first_non_zero = 0;
+  while (first_non_zero < filter_length && filter_values[first_non_zero] == 0)
+    first_non_zero++;
+
+  if (first_non_zero < filter_length) {
+    // Here we have at least one non-zero factor.
+    int last_non_zero = filter_length - 1;
+    while (last_non_zero >= 0 && filter_values[last_non_zero] == 0)
+      last_non_zero--;
+
+    filter_offset += first_non_zero;
+    filter_length = last_non_zero + 1 - first_non_zero;
+    SkASSERT(filter_length > 0);
+
+    for (int i = first_non_zero; i <= last_non_zero; i++)
+      filter_values_.push_back(filter_values[i]);
+  } else {
+    // Here all the factors were zeroes.
+    filter_length = 0;
+  }
+
+  FilterInstance instance;
+
+  // We pushed filter_length elements onto filter_values_
+  instance.data_location =
+      (static_cast<int>(filter_values_.size()) - filter_length);
+  instance.offset = filter_offset;
+  instance.trimmed_length = filter_length;
+  instance.length = filter_size;
+  filters_.push_back(instance);
+
+  max_filter_ = std::max(max_filter_, filter_length);
+}
+
+const ConvolutionFilter1D::Fixed* ConvolutionFilter1D::GetSingleFilter(
+    int* specified_filter_length,
+    int* filter_offset,
+    int* filter_length) const {
+  const FilterInstance& filter = filters_[0];
+  *filter_offset = filter.offset;
+  *filter_length = filter.trimmed_length;
+  *specified_filter_length = filter.length;
+  if (filter.trimmed_length == 0)
+    return NULL;
+
+  return &filter_values_[filter.data_location];
+}
+
+typedef void (*ConvolveVertically_pointer)(
+    const ConvolutionFilter1D::Fixed* filter_values,
+    int filter_length,
+    unsigned char* const* source_data_rows,
+    int pixel_width,
+    unsigned char* out_row,
+    bool has_alpha);
+typedef void (*Convolve4RowsHorizontally_pointer)(
+    const unsigned char* src_data[4],
+    const ConvolutionFilter1D& filter,
+    unsigned char* out_row[4]);
+typedef void (*ConvolveHorizontally_pointer)(const unsigned char* src_data,
+                                             const ConvolutionFilter1D& filter,
+                                             unsigned char* out_row,
+                                             bool has_alpha);
+
+struct ConvolveProcs {
+  // This is how many extra pixels may be read by the
+  // conolve*horizontally functions.
+  int extra_horizontal_reads;
+  ConvolveVertically_pointer convolve_vertically;
+  Convolve4RowsHorizontally_pointer convolve_4rows_horizontally;
+  ConvolveHorizontally_pointer convolve_horizontally;
+};
+
+void SetupSIMD(ConvolveProcs* procs) {
+#ifdef SIMD_SSE2
+  procs->extra_horizontal_reads = 3;
+  procs->convolve_vertically = &ConvolveVertically_SSE2;
+  procs->convolve_4rows_horizontally = &Convolve4RowsHorizontally_SSE2;
+  procs->convolve_horizontally = &ConvolveHorizontally_SSE2;
+#elif defined SIMD_MIPS_DSPR2
+  procs->extra_horizontal_reads = 3;
+  procs->convolve_vertically = &ConvolveVertically_mips_dspr2;
+  procs->convolve_horizontally = &ConvolveHorizontally_mips_dspr2;
+#endif
+}
+
+void BGRAConvolve2D(const unsigned char* source_data,
+                    int source_byte_row_stride,
+                    bool source_has_alpha,
+                    const ConvolutionFilter1D& filter_x,
+                    const ConvolutionFilter1D& filter_y,
+                    int output_byte_row_stride,
+                    unsigned char* output,
+                    bool use_simd_if_possible) {
+  ConvolveProcs simd;
+  simd.extra_horizontal_reads = 0;
+  simd.convolve_vertically = NULL;
+  simd.convolve_4rows_horizontally = NULL;
+  simd.convolve_horizontally = NULL;
+  if (use_simd_if_possible) {
+    SetupSIMD(&simd);
+  }
+
+  int max_y_filter_size = filter_y.max_filter();
+
+  // The next row in the input that we will generate a horizontally
+  // convolved row for. If the filter doesn't start at the beginning of the
+  // image (this is the case when we are only resizing a subset), then we
+  // don't want to generate any output rows before that. Compute the starting
+  // row for convolution as the first pixel for the first vertical filter.
+  int filter_offset, filter_length;
+  const ConvolutionFilter1D::Fixed* filter_values =
+      filter_y.FilterForValue(0, &filter_offset, &filter_length);
+  int next_x_row = filter_offset;
+
+  // We loop over each row in the input doing a horizontal convolution. This
+  // will result in a horizontally convolved image. We write the results into
+  // a circular buffer of convolved rows and do vertical convolution as rows
+  // are available. This prevents us from having to store the entire
+  // intermediate image and helps cache coherency.
+  // We will need four extra rows to allow horizontal convolution could be done
+  // simultaneously. We also padding each row in row buffer to be aligned-up to
+  // 16 bytes.
+  // TODO(jiesun): We do not use aligned load from row buffer in vertical
+  // convolution pass yet. Somehow Windows does not like it.
+  int row_buffer_width = (filter_x.num_values() + 15) & ~0xF;
+  int row_buffer_height =
+      max_y_filter_size + (simd.convolve_4rows_horizontally ? 4 : 0);
+  CircularRowBuffer row_buffer(row_buffer_width, row_buffer_height,
+                               filter_offset);
+
+  // Loop over every possible output row, processing just enough horizontal
+  // convolutions to run each subsequent vertical convolution.
+  SkASSERT(output_byte_row_stride >= filter_x.num_values() * 4);
+  int num_output_rows = filter_y.num_values();
+
+  // We need to check which is the last line to convolve before we advance 4
+  // lines in one iteration.
+  int last_filter_offset, last_filter_length;
+
+  // SSE2 can access up to 3 extra pixels past the end of the
+  // buffer. At the bottom of the image, we have to be careful
+  // not to access data past the end of the buffer. Normally
+  // we fall back to the C++ implementation for the last row.
+  // If the last row is less than 3 pixels wide, we may have to fall
+  // back to the C++ version for more rows. Compute how many
+  // rows we need to avoid the SSE implementation for here.
+  filter_x.FilterForValue(filter_x.num_values() - 1, &last_filter_offset,
+                          &last_filter_length);
+  int avoid_simd_rows =
+      1 +
+      simd.extra_horizontal_reads / (last_filter_offset + last_filter_length);
+
+  filter_y.FilterForValue(num_output_rows - 1, &last_filter_offset,
+                          &last_filter_length);
+
+  for (int out_y = 0; out_y < num_output_rows; out_y++) {
+    filter_values =
+        filter_y.FilterForValue(out_y, &filter_offset, &filter_length);
+
+    // Generate output rows until we have enough to run the current filter.
+    while (next_x_row < filter_offset + filter_length) {
+      if (simd.convolve_4rows_horizontally &&
+          next_x_row + 3 <
+              last_filter_offset + last_filter_length - avoid_simd_rows) {
+        const unsigned char* src[4];
+        unsigned char* out_row[4];
+        for (int i = 0; i < 4; ++i) {
+          src[i] = &source_data[(next_x_row + i) * source_byte_row_stride];
+          out_row[i] = row_buffer.AdvanceRow();
+        }
+        simd.convolve_4rows_horizontally(src, filter_x, out_row);
+        next_x_row += 4;
+      } else {
+        // Check if we need to avoid SSE2 for this row.
+        if (simd.convolve_horizontally &&
+            next_x_row <
+                last_filter_offset + last_filter_length - avoid_simd_rows) {
+          simd.convolve_horizontally(
+              &source_data[next_x_row * source_byte_row_stride], filter_x,
+              row_buffer.AdvanceRow(), source_has_alpha);
+        } else {
+          if (source_has_alpha) {
+            ConvolveHorizontally<true>(
+                &source_data[next_x_row * source_byte_row_stride], filter_x,
+                row_buffer.AdvanceRow());
+          } else {
+            ConvolveHorizontally<false>(
+                &source_data[next_x_row * source_byte_row_stride], filter_x,
+                row_buffer.AdvanceRow());
+          }
+        }
+        next_x_row++;
+      }
+    }
+
+    // Compute where in the output image this row of final data will go.
+    unsigned char* cur_output_row = &output[out_y * output_byte_row_stride];
+
+    // Get the list of rows that the circular buffer has, in order.
+    int first_row_in_circular_buffer;
+    unsigned char* const* rows_to_convolve =
+        row_buffer.GetRowAddresses(&first_row_in_circular_buffer);
+
+    // Now compute the start of the subset of those rows that the filter
+    // needs.
+    unsigned char* const* first_row_for_filter =
+        &rows_to_convolve[filter_offset - first_row_in_circular_buffer];
+
+    if (simd.convolve_vertically) {
+      simd.convolve_vertically(filter_values, filter_length,
+                               first_row_for_filter, filter_x.num_values(),
+                               cur_output_row, source_has_alpha);
+    } else {
+      ConvolveVertically(filter_values, filter_length, first_row_for_filter,
+                         filter_x.num_values(), cur_output_row,
+                         source_has_alpha);
+    }
+  }
+}
+
+void SingleChannelConvolveX1D(const unsigned char* source_data,
+                              int source_byte_row_stride,
+                              int input_channel_index,
+                              int input_channel_count,
+                              const ConvolutionFilter1D& filter,
+                              const SkISize& image_size,
+                              unsigned char* output,
+                              int output_byte_row_stride,
+                              int output_channel_index,
+                              int output_channel_count,
+                              bool absolute_values) {
+  int filter_offset, filter_length, filter_size;
+  // Very much unlike BGRAConvolve2D, here we expect to have the same filter
+  // for all pixels.
+  const ConvolutionFilter1D::Fixed* filter_values =
+      filter.GetSingleFilter(&filter_size, &filter_offset, &filter_length);
+
+  if (filter_values == NULL || image_size.width() < filter_size) {
+    NOTREACHED();
+    return;
+  }
+
+  int centrepoint = filter_length / 2;
+  if (filter_size - filter_offset != 2 * filter_offset) {
+    // This means the original filter was not symmetrical AND
+    // got clipped from one side more than from the other.
+    centrepoint = filter_size / 2 - filter_offset;
+  }
+
+  const unsigned char* source_data_row = source_data;
+  unsigned char* output_row = output;
+
+  for (int r = 0; r < image_size.height(); ++r) {
+    unsigned char* target_byte = output_row + output_channel_index;
+    // Process the lead part, padding image to the left with the first pixel.
+    int c = 0;
+    for (; c < centrepoint; ++c, target_byte += output_channel_count) {
+      int accval = 0;
+      int i = 0;
+      int pixel_byte_index = input_channel_index;
+      for (; i < centrepoint - c; ++i)  // Padding part.
+        accval += filter_values[i] * source_data_row[pixel_byte_index];
+
+      for (; i < filter_length; ++i, pixel_byte_index += input_channel_count)
+        accval += filter_values[i] * source_data_row[pixel_byte_index];
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+
+    // Now for the main event.
+    for (; c < image_size.width() - centrepoint;
+         ++c, target_byte += output_channel_count) {
+      int accval = 0;
+      int pixel_byte_index =
+          (c - centrepoint) * input_channel_count + input_channel_index;
+
+      for (int i = 0; i < filter_length;
+           ++i, pixel_byte_index += input_channel_count) {
+        accval += filter_values[i] * source_data_row[pixel_byte_index];
+      }
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+
+    for (; c < image_size.width(); ++c, target_byte += output_channel_count) {
+      int accval = 0;
+      int overlap_taps = image_size.width() - c + centrepoint;
+      int pixel_byte_index =
+          (c - centrepoint) * input_channel_count + input_channel_index;
+      int i = 0;
+      for (; i < overlap_taps - 1; ++i, pixel_byte_index += input_channel_count)
+        accval += filter_values[i] * source_data_row[pixel_byte_index];
+
+      for (; i < filter_length; ++i)
+        accval += filter_values[i] * source_data_row[pixel_byte_index];
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+
+    source_data_row += source_byte_row_stride;
+    output_row += output_byte_row_stride;
+  }
+}
+
+void SingleChannelConvolveY1D(const unsigned char* source_data,
+                              int source_byte_row_stride,
+                              int input_channel_index,
+                              int input_channel_count,
+                              const ConvolutionFilter1D& filter,
+                              const SkISize& image_size,
+                              unsigned char* output,
+                              int output_byte_row_stride,
+                              int output_channel_index,
+                              int output_channel_count,
+                              bool absolute_values) {
+  int filter_offset, filter_length, filter_size;
+  // Very much unlike BGRAConvolve2D, here we expect to have the same filter
+  // for all pixels.
+  const ConvolutionFilter1D::Fixed* filter_values =
+      filter.GetSingleFilter(&filter_size, &filter_offset, &filter_length);
+
+  if (filter_values == NULL || image_size.height() < filter_size) {
+    NOTREACHED();
+    return;
+  }
+
+  int centrepoint = filter_length / 2;
+  if (filter_size - filter_offset != 2 * filter_offset) {
+    // This means the original filter was not symmetrical AND
+    // got clipped from one side more than from the other.
+    centrepoint = filter_size / 2 - filter_offset;
+  }
+
+  for (int c = 0; c < image_size.width(); ++c) {
+    unsigned char* target_byte =
+        output + c * output_channel_count + output_channel_index;
+    int r = 0;
+
+    for (; r < centrepoint; ++r, target_byte += output_byte_row_stride) {
+      int accval = 0;
+      int i = 0;
+      int pixel_byte_index = c * input_channel_count + input_channel_index;
+
+      for (; i < centrepoint - r; ++i)  // Padding part.
+        accval += filter_values[i] * source_data[pixel_byte_index];
+
+      for (; i < filter_length; ++i, pixel_byte_index += source_byte_row_stride)
+        accval += filter_values[i] * source_data[pixel_byte_index];
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+
+    for (; r < image_size.height() - centrepoint;
+         ++r, target_byte += output_byte_row_stride) {
+      int accval = 0;
+      int pixel_byte_index = (r - centrepoint) * source_byte_row_stride +
+                             c * input_channel_count + input_channel_index;
+      for (int i = 0; i < filter_length;
+           ++i, pixel_byte_index += source_byte_row_stride) {
+        accval += filter_values[i] * source_data[pixel_byte_index];
+      }
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+
+    for (; r < image_size.height();
+         ++r, target_byte += output_byte_row_stride) {
+      int accval = 0;
+      int overlap_taps = image_size.height() - r + centrepoint;
+      int pixel_byte_index = (r - centrepoint) * source_byte_row_stride +
+                             c * input_channel_count + input_channel_index;
+      int i = 0;
+      for (; i < overlap_taps - 1;
+           ++i, pixel_byte_index += source_byte_row_stride) {
+        accval += filter_values[i] * source_data[pixel_byte_index];
+      }
+
+      for (; i < filter_length; ++i)
+        accval += filter_values[i] * source_data[pixel_byte_index];
+
+      *target_byte = BringBackTo8(accval, absolute_values);
+    }
+  }
+}
+
+void SetUpGaussianConvolutionKernel(ConvolutionFilter1D* filter,
+                                    float kernel_sigma,
+                                    bool derivative) {
+  DCHECK(filter != NULL);
+  DCHECK_GT(kernel_sigma, 0.0);
+  const int tail_length = static_cast<int>(4.0f * kernel_sigma + 0.5f);
+  const int kernel_size = tail_length * 2 + 1;
+  const float sigmasq = kernel_sigma * kernel_sigma;
+  std::vector<float> kernel_weights(kernel_size, 0.0);
+  float kernel_sum = 1.0f;
+
+  kernel_weights[tail_length] = 1.0f;
+
+  for (int ii = 1; ii <= tail_length; ++ii) {
+    float v = std::exp(-0.5f * ii * ii / sigmasq);
+    kernel_weights[tail_length + ii] = v;
+    kernel_weights[tail_length - ii] = v;
+    kernel_sum += 2.0f * v;
+  }
+
+  for (int i = 0; i < kernel_size; ++i)
+    kernel_weights[i] /= kernel_sum;
+
+  if (derivative) {
+    kernel_weights[tail_length] = 0.0;
+    for (int ii = 1; ii <= tail_length; ++ii) {
+      float v = sigmasq * kernel_weights[tail_length + ii] / ii;
+      kernel_weights[tail_length + ii] = v;
+      kernel_weights[tail_length - ii] = -v;
+    }
+  }
+
+  filter->AddFilter(0, &kernel_weights[0], kernel_weights.size());
+}
+
+}  // namespace skia