convolver.h

// Copyright (c) 2012 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.

#ifndef SKIA_EXT_CONVOLVER_H_
#define SKIA_EXT_CONVOLVER_H_

#include <cmath>
#include <vector>

#include "base/basictypes.h"
#include "base/cpu.h"
#include "third_party/skia/include/core/SkSize.h"
#include "third_party/skia/include/core/SkTypes.h"

// We can build SSE2 optimized versions for all x86 CPUs
// except when building for the IOS emulator.
#if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_IOS)
#define SIMD_SSE2 1
#define SIMD_PADDING 8  // 8 * int16
#endif

#if defined (ARCH_CPU_MIPS_FAMILY) && \
    defined(__mips_dsp) && (__mips_dsp_rev >= 2)
#define SIMD_MIPS_DSPR2 1
#endif
// avoid confusion with Mac OS X's math library (Carbon)
#if defined(__APPLE__)
#undef FloatToFixed
#undef FixedToFloat
#endif

namespace skia {

// Represents a filter in one dimension. Each output pixel has one entry in this
// object for the filter values contributing to it. You build up the filter
// list by calling AddFilter for each output pixel (in order).
//
// We do 2-dimensional convolution by first convolving each row by one
// ConvolutionFilter1D, then convolving each column by another one.
//
// Entries are stored in fixed point, shifted left by kShiftBits.
class ConvolutionFilter1D {
 public:
  typedef short Fixed;

  // The number of bits that fixed point values are shifted by.
  enum { kShiftBits = 14 };

  SK_API ConvolutionFilter1D();
  SK_API ~ConvolutionFilter1D();

  // Convert between floating point and our fixed point representation.
  static Fixed FloatToFixed(float f) {
    return static_cast<Fixed>(f * (1 << kShiftBits));
  }
  static unsigned char FixedToChar(Fixed x) {
    return static_cast<unsigned char>(x >> kShiftBits);
  }
  static float FixedToFloat(Fixed x) {
    // The cast relies on Fixed being a short, implying that on
    // the platforms we care about all (16) bits will fit into
    // the mantissa of a (32-bit) float.
    COMPILE_ASSERT(sizeof(Fixed) == 2, fixed_type_should_fit_in_float_mantissa);
    float raw = static_cast<float>(x);
    return ldexpf(raw, -kShiftBits);
  }

  // Returns the maximum pixel span of a filter.
  int max_filter() const { return max_filter_; }

  // Returns the number of filters in this filter. This is the dimension of the
  // output image.
  int num_values() const { return static_cast<int>(filters_.size()); }

  // Appends the given list of scaling values for generating a given output
  // pixel. |filter_offset| is the distance from the edge of the image to where
  // the scaling factors start. The scaling factors apply to the source pixels
  // starting from this position, and going for the next |filter_length| pixels.
  //
  // You will probably want to make sure your input is normalized (that is,
  // all entries in |filter_values| sub to one) to prevent affecting the overall
  // brighness of the image.
  //
  // The filter_length must be > 0.
  //
  // This version will automatically convert your input to fixed point.
  SK_API void AddFilter(int filter_offset,
                        const float* filter_values,
                        int filter_length);

  // Same as the above version, but the input is already fixed point.
  void AddFilter(int filter_offset,
                 const Fixed* filter_values,
                 int filter_length);

  // Retrieves a filter for the given |value_offset|, a position in the output
  // image in the direction we're convolving. The offset and length of the
  // filter values are put into the corresponding out arguments (see AddFilter
  // above for what these mean), and a pointer to the first scaling factor is
  // returned. There will be |filter_length| values in this array.
  inline const Fixed* FilterForValue(int value_offset,
                                     int* filter_offset,
                                     int* filter_length) const {
    const FilterInstance& filter = filters_[value_offset];
    *filter_offset = filter.offset;
    *filter_length = filter.trimmed_length;
    if (filter.trimmed_length == 0) {
      return NULL;
    }
    return &filter_values_[filter.data_location];
  }

  // Retrieves the filter for the offset 0, presumed to be the one and only.
  // The offset and length of the filter values are put into the corresponding
  // out arguments (see AddFilter). Note that |filter_legth| and
  // |specified_filter_length| may be different if leading/trailing zeros of the
  // original floating point form were clipped.
  // There will be |filter_length| values in the return array.
  // Returns NULL if the filter is 0-length (for instance when all floating
  // point values passed to AddFilter were clipped to 0).
  SK_API const Fixed* GetSingleFilter(int* specified_filter_length,
                                      int* filter_offset,
                                      int* filter_length) const;

  inline void PaddingForSIMD() {
    // Padding |padding_count| of more dummy coefficients after the coefficients
    // of last filter to prevent SIMD instructions which load 8 or 16 bytes
    // together to access invalid memory areas. We are not trying to align the
    // coefficients right now due to the opaqueness of <vector> implementation.
    // This has to be done after all |AddFilter| calls.
#ifdef SIMD_PADDING
    for (int i = 0; i < SIMD_PADDING; ++i)
      filter_values_.push_back(static_cast<Fixed>(0));
#endif
  }

 private:
  struct FilterInstance {
    // Offset within filter_values for this instance of the filter.
    int data_location;

    // Distance from the left of the filter to the center. IN PIXELS
    int offset;

    // Number of values in this filter instance.
    int trimmed_length;

    // Filter length as specified. Note that this may be different from
    // 'trimmed_length' if leading/trailing zeros of the original floating
    // point form were clipped differently on each tail.
    int length;
  };

  // Stores the information for each filter added to this class.
  std::vector<FilterInstance> filters_;

  // We store all the filter values in this flat list, indexed by
  // |FilterInstance.data_location| to avoid the mallocs required for storing
  // each one separately.
  std::vector<Fixed> filter_values_;

  // The maximum size of any filter we've added.
  int max_filter_;
};

// Does a two-dimensional convolution on the given source image.
//
// It is assumed the source pixel offsets referenced in the input filters
// reference only valid pixels, so the source image size is not required. Each
// row of the source image starts |source_byte_row_stride| after the previous
// one (this allows you to have rows with some padding at the end).
//
// The result will be put into the given output buffer. The destination image
// size will be xfilter.num_values() * yfilter.num_values() pixels. It will be
// in rows of exactly xfilter.num_values() * 4 bytes.
//
// |source_has_alpha| is a hint that allows us to avoid doing computations on
// the alpha channel if the image is opaque. If you don't know, set this to
// true and it will work properly, but setting this to false will be a few
// percent faster if you know the image is opaque.
//
// The layout in memory is assumed to be 4-bytes per pixel in B-G-R-A order
// (this is ARGB when loaded into 32-bit words on a little-endian machine).
SK_API void BGRAConvolve2D(const unsigned char* source_data,
                           int source_byte_row_stride,
                           bool source_has_alpha,
                           const ConvolutionFilter1D& xfilter,
                           const ConvolutionFilter1D& yfilter,
                           int output_byte_row_stride,
                           unsigned char* output,
                           bool use_simd_if_possible);

// Does a 1D convolution of the given source image along the X dimension on
// a single channel of the bitmap.
//
// The function uses the same convolution kernel for each pixel. That kernel
// must be added to |filter| at offset 0. This is a most straightforward
// implementation of convolution, intended chiefly for development purposes.
SK_API 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);

// Does a 1D convolution of the given source image along the Y dimension on
// a single channel of the bitmap.
SK_API 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);

// Set up the |filter| instance with a gaussian kernel. |kernel_sigma| is the
// parameter of gaussian. If |derivative| is true, the kernel will be that of
// the first derivative. Intended for use with the two routines above.
SK_API void SetUpGaussianConvolutionKernel(ConvolutionFilter1D* filter,
                                           float kernel_sigma,
                                           bool derivative);

}  // namespace skia

#endif  // SKIA_EXT_CONVOLVER_H_