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865 lines
35 KiB
C++
865 lines
35 KiB
C++
// Copyright (c) 2011 The Chromium Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file.
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#include "convolver.h"
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#include <algorithm>
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#include "nsAlgorithm.h"
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#include "skia/SkTypes.h"
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// note: SIMD_SSE2 is not enabled because of bugs, apparently
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#if defined(SIMD_SSE2)
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#include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h
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#endif
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namespace skia {
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namespace {
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// Converts the argument to an 8-bit unsigned value by clamping to the range
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// 0-255.
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inline unsigned char ClampTo8(int a) {
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if (static_cast<unsigned>(a) < 256)
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return a; // Avoid the extra check in the common case.
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if (a < 0)
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return 0;
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return 255;
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}
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// Stores a list of rows in a circular buffer. The usage is you write into it
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// by calling AdvanceRow. It will keep track of which row in the buffer it
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// should use next, and the total number of rows added.
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class CircularRowBuffer {
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public:
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// The number of pixels in each row is given in |source_row_pixel_width|.
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// The maximum number of rows needed in the buffer is |max_y_filter_size|
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// (we only need to store enough rows for the biggest filter).
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//
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// We use the |first_input_row| to compute the coordinates of all of the
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// following rows returned by Advance().
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CircularRowBuffer(int dest_row_pixel_width, int max_y_filter_size,
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int first_input_row)
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: row_byte_width_(dest_row_pixel_width * 4),
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num_rows_(max_y_filter_size),
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next_row_(0),
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next_row_coordinate_(first_input_row) {
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buffer_.resize(row_byte_width_ * max_y_filter_size);
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row_addresses_.resize(num_rows_);
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}
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// Moves to the next row in the buffer, returning a pointer to the beginning
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// of it.
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unsigned char* AdvanceRow() {
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unsigned char* row = &buffer_[next_row_ * row_byte_width_];
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next_row_coordinate_++;
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// Set the pointer to the next row to use, wrapping around if necessary.
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next_row_++;
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if (next_row_ == num_rows_)
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next_row_ = 0;
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return row;
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}
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// Returns a pointer to an "unrolled" array of rows. These rows will start
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// at the y coordinate placed into |*first_row_index| and will continue in
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// order for the maximum number of rows in this circular buffer.
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//
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// The |first_row_index_| may be negative. This means the circular buffer
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// starts before the top of the image (it hasn't been filled yet).
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unsigned char* const* GetRowAddresses(int* first_row_index) {
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// Example for a 4-element circular buffer holding coords 6-9.
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// Row 0 Coord 8
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// Row 1 Coord 9
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// Row 2 Coord 6 <- next_row_ = 2, next_row_coordinate_ = 10.
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// Row 3 Coord 7
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//
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// The "next" row is also the first (lowest) coordinate. This computation
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// may yield a negative value, but that's OK, the math will work out
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// since the user of this buffer will compute the offset relative
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// to the first_row_index and the negative rows will never be used.
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*first_row_index = next_row_coordinate_ - num_rows_;
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int cur_row = next_row_;
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for (int i = 0; i < num_rows_; i++) {
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row_addresses_[i] = &buffer_[cur_row * row_byte_width_];
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// Advance to the next row, wrapping if necessary.
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cur_row++;
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if (cur_row == num_rows_)
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cur_row = 0;
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}
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return &row_addresses_[0];
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}
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private:
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// The buffer storing the rows. They are packed, each one row_byte_width_.
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std::vector<unsigned char> buffer_;
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// Number of bytes per row in the |buffer_|.
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int row_byte_width_;
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// The number of rows available in the buffer.
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int num_rows_;
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// The next row index we should write into. This wraps around as the
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// circular buffer is used.
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int next_row_;
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// The y coordinate of the |next_row_|. This is incremented each time a
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// new row is appended and does not wrap.
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int next_row_coordinate_;
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// Buffer used by GetRowAddresses().
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std::vector<unsigned char*> row_addresses_;
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};
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// Convolves horizontally along a single row. The row data is given in
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// |src_data| and continues for the num_values() of the filter.
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template<bool has_alpha>
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void ConvolveHorizontally(const unsigned char* src_data,
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const ConvolutionFilter1D& filter,
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unsigned char* out_row) {
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// Loop over each pixel on this row in the output image.
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int num_values = filter.num_values();
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for (int out_x = 0; out_x < num_values; out_x++) {
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// Get the filter that determines the current output pixel.
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int filter_offset, filter_length;
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const ConvolutionFilter1D::Fixed* filter_values =
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filter.FilterForValue(out_x, &filter_offset, &filter_length);
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// Compute the first pixel in this row that the filter affects. It will
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// touch |filter_length| pixels (4 bytes each) after this.
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const unsigned char* row_to_filter = &src_data[filter_offset * 4];
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// Apply the filter to the row to get the destination pixel in |accum|.
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int accum[4] = {0};
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for (int filter_x = 0; filter_x < filter_length; filter_x++) {
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ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x];
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accum[0] += cur_filter * row_to_filter[filter_x * 4 + 0];
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accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1];
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accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2];
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if (has_alpha)
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accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3];
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}
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// Bring this value back in range. All of the filter scaling factors
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// are in fixed point with kShiftBits bits of fractional part.
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accum[0] >>= ConvolutionFilter1D::kShiftBits;
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accum[1] >>= ConvolutionFilter1D::kShiftBits;
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accum[2] >>= ConvolutionFilter1D::kShiftBits;
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if (has_alpha)
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accum[3] >>= ConvolutionFilter1D::kShiftBits;
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// Store the new pixel.
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out_row[out_x * 4 + 0] = ClampTo8(accum[0]);
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out_row[out_x * 4 + 1] = ClampTo8(accum[1]);
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out_row[out_x * 4 + 2] = ClampTo8(accum[2]);
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if (has_alpha)
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out_row[out_x * 4 + 3] = ClampTo8(accum[3]);
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}
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}
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// Does vertical convolution to produce one output row. The filter values and
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// length are given in the first two parameters. These are applied to each
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// of the rows pointed to in the |source_data_rows| array, with each row
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// being |pixel_width| wide.
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//
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// The output must have room for |pixel_width * 4| bytes.
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template<bool has_alpha>
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void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
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int filter_length,
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unsigned char* const* source_data_rows,
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int pixel_width,
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unsigned char* out_row) {
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// We go through each column in the output and do a vertical convolution,
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// generating one output pixel each time.
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for (int out_x = 0; out_x < pixel_width; out_x++) {
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// Compute the number of bytes over in each row that the current column
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// we're convolving starts at. The pixel will cover the next 4 bytes.
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int byte_offset = out_x * 4;
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// Apply the filter to one column of pixels.
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int accum[4] = {0};
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for (int filter_y = 0; filter_y < filter_length; filter_y++) {
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ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y];
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accum[0] += cur_filter * source_data_rows[filter_y][byte_offset + 0];
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accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1];
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accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2];
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if (has_alpha)
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accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3];
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}
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// Bring this value back in range. All of the filter scaling factors
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// are in fixed point with kShiftBits bits of precision.
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accum[0] >>= ConvolutionFilter1D::kShiftBits;
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accum[1] >>= ConvolutionFilter1D::kShiftBits;
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accum[2] >>= ConvolutionFilter1D::kShiftBits;
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if (has_alpha)
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accum[3] >>= ConvolutionFilter1D::kShiftBits;
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// Store the new pixel.
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out_row[byte_offset + 0] = ClampTo8(accum[0]);
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out_row[byte_offset + 1] = ClampTo8(accum[1]);
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out_row[byte_offset + 2] = ClampTo8(accum[2]);
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if (has_alpha) {
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unsigned char alpha = ClampTo8(accum[3]);
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// Make sure the alpha channel doesn't come out smaller than any of the
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// color channels. We use premultipled alpha channels, so this should
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// never happen, but rounding errors will cause this from time to time.
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// These "impossible" colors will cause overflows (and hence random pixel
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// values) when the resulting bitmap is drawn to the screen.
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//
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// We only need to do this when generating the final output row (here).
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int max_color_channel = NS_MAX(out_row[byte_offset + 0],
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NS_MAX(out_row[byte_offset + 1], out_row[byte_offset + 2]));
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if (alpha < max_color_channel)
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out_row[byte_offset + 3] = max_color_channel;
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else
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out_row[byte_offset + 3] = alpha;
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} else {
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// No alpha channel, the image is opaque.
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out_row[byte_offset + 3] = 0xff;
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}
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}
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}
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// Convolves horizontally along a single row. The row data is given in
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// |src_data| and continues for the num_values() of the filter.
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void ConvolveHorizontally_SSE2(const unsigned char* src_data,
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const ConvolutionFilter1D& filter,
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unsigned char* out_row) {
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#if defined(SIMD_SSE2)
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int num_values = filter.num_values();
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int filter_offset, filter_length;
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__m128i zero = _mm_setzero_si128();
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__m128i mask[4];
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// |mask| will be used to decimate all extra filter coefficients that are
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// loaded by SIMD when |filter_length| is not divisible by 4.
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// mask[0] is not used in following algorithm.
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mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
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mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
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mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);
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// Output one pixel each iteration, calculating all channels (RGBA) together.
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for (int out_x = 0; out_x < num_values; out_x++) {
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const ConvolutionFilter1D::Fixed* filter_values =
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filter.FilterForValue(out_x, &filter_offset, &filter_length);
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__m128i accum = _mm_setzero_si128();
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// Compute the first pixel in this row that the filter affects. It will
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// touch |filter_length| pixels (4 bytes each) after this.
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const __m128i* row_to_filter =
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reinterpret_cast<const __m128i*>(&src_data[filter_offset << 2]);
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// We will load and accumulate with four coefficients per iteration.
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for (int filter_x = 0; filter_x < filter_length >> 2; filter_x++) {
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// Load 4 coefficients => duplicate 1st and 2nd of them for all channels.
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__m128i coeff, coeff16;
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// [16] xx xx xx xx c3 c2 c1 c0
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coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
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// [16] xx xx xx xx c1 c1 c0 c0
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coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
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// [16] c1 c1 c1 c1 c0 c0 c0 c0
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coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
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// Load four pixels => unpack the first two pixels to 16 bits =>
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// multiply with coefficients => accumulate the convolution result.
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// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
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__m128i src8 = _mm_loadu_si128(row_to_filter);
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// [16] a1 b1 g1 r1 a0 b0 g0 r0
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__m128i src16 = _mm_unpacklo_epi8(src8, zero);
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__m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
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__m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
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// [32] a0*c0 b0*c0 g0*c0 r0*c0
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__m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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// [32] a1*c1 b1*c1 g1*c1 r1*c1
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t = _mm_unpackhi_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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// Duplicate 3rd and 4th coefficients for all channels =>
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// unpack the 3rd and 4th pixels to 16 bits => multiply with coefficients
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// => accumulate the convolution results.
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// [16] xx xx xx xx c3 c3 c2 c2
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coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
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// [16] c3 c3 c3 c3 c2 c2 c2 c2
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coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
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// [16] a3 g3 b3 r3 a2 g2 b2 r2
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src16 = _mm_unpackhi_epi8(src8, zero);
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mul_hi = _mm_mulhi_epi16(src16, coeff16);
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mul_lo = _mm_mullo_epi16(src16, coeff16);
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// [32] a2*c2 b2*c2 g2*c2 r2*c2
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t = _mm_unpacklo_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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// [32] a3*c3 b3*c3 g3*c3 r3*c3
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t = _mm_unpackhi_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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// Advance the pixel and coefficients pointers.
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row_to_filter += 1;
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filter_values += 4;
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}
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// When |filter_length| is not divisible by 4, we need to decimate some of
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// the filter coefficient that was loaded incorrectly to zero; Other than
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// that the algorithm is same with above, exceot that the 4th pixel will be
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// always absent.
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int r = filter_length&3;
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if (r) {
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// Note: filter_values must be padded to align_up(filter_offset, 8).
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__m128i coeff, coeff16;
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coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
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// Mask out extra filter taps.
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coeff = _mm_and_si128(coeff, mask[r]);
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coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
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coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
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// Note: line buffer must be padded to align_up(filter_offset, 16).
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// We resolve this by use C-version for the last horizontal line.
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__m128i src8 = _mm_loadu_si128(row_to_filter);
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__m128i src16 = _mm_unpacklo_epi8(src8, zero);
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__m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
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__m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
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__m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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t = _mm_unpackhi_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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src16 = _mm_unpackhi_epi8(src8, zero);
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coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
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coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
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mul_hi = _mm_mulhi_epi16(src16, coeff16);
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mul_lo = _mm_mullo_epi16(src16, coeff16);
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t = _mm_unpacklo_epi16(mul_lo, mul_hi);
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accum = _mm_add_epi32(accum, t);
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}
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// Shift right for fixed point implementation.
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accum = _mm_srai_epi32(accum, ConvolutionFilter1D::kShiftBits);
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// Packing 32 bits |accum| to 16 bits per channel (signed saturation).
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accum = _mm_packs_epi32(accum, zero);
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// Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
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accum = _mm_packus_epi16(accum, zero);
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// Store the pixel value of 32 bits.
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*(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum);
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out_row += 4;
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}
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#endif
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}
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// Convolves horizontally along four rows. The row data is given in
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// |src_data| and continues for the num_values() of the filter.
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// The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please
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// refer to that function for detailed comments.
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void ConvolveHorizontally4_SSE2(const unsigned char* src_data[4],
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const ConvolutionFilter1D& filter,
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unsigned char* out_row[4]) {
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#if defined(SIMD_SSE2)
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int num_values = filter.num_values();
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int filter_offset, filter_length;
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__m128i zero = _mm_setzero_si128();
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__m128i mask[4];
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// |mask| will be used to decimate all extra filter coefficients that are
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// loaded by SIMD when |filter_length| is not divisible by 4.
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// mask[0] is not used in following algorithm.
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mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
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mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
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mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);
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// Output one pixel each iteration, calculating all channels (RGBA) together.
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for (int out_x = 0; out_x < num_values; out_x++) {
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const ConvolutionFilter1D::Fixed* filter_values =
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filter.FilterForValue(out_x, &filter_offset, &filter_length);
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// four pixels in a column per iteration.
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__m128i accum0 = _mm_setzero_si128();
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__m128i accum1 = _mm_setzero_si128();
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__m128i accum2 = _mm_setzero_si128();
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__m128i accum3 = _mm_setzero_si128();
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int start = (filter_offset<<2);
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// We will load and accumulate with four coefficients per iteration.
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for (int filter_x = 0; filter_x < (filter_length >> 2); filter_x++) {
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__m128i coeff, coeff16lo, coeff16hi;
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// [16] xx xx xx xx c3 c2 c1 c0
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coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
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// [16] xx xx xx xx c1 c1 c0 c0
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coeff16lo = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
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// [16] c1 c1 c1 c1 c0 c0 c0 c0
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coeff16lo = _mm_unpacklo_epi16(coeff16lo, coeff16lo);
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// [16] xx xx xx xx c3 c3 c2 c2
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coeff16hi = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
|
|
// [16] c3 c3 c3 c3 c2 c2 c2 c2
|
|
coeff16hi = _mm_unpacklo_epi16(coeff16hi, coeff16hi);
|
|
|
|
__m128i src8, src16, mul_hi, mul_lo, t;
|
|
|
|
#define ITERATION(src, accum) \
|
|
src8 = _mm_loadu_si128(reinterpret_cast<const __m128i*>(src)); \
|
|
src16 = _mm_unpacklo_epi8(src8, zero); \
|
|
mul_hi = _mm_mulhi_epi16(src16, coeff16lo); \
|
|
mul_lo = _mm_mullo_epi16(src16, coeff16lo); \
|
|
t = _mm_unpacklo_epi16(mul_lo, mul_hi); \
|
|
accum = _mm_add_epi32(accum, t); \
|
|
t = _mm_unpackhi_epi16(mul_lo, mul_hi); \
|
|
accum = _mm_add_epi32(accum, t); \
|
|
src16 = _mm_unpackhi_epi8(src8, zero); \
|
|
mul_hi = _mm_mulhi_epi16(src16, coeff16hi); \
|
|
mul_lo = _mm_mullo_epi16(src16, coeff16hi); \
|
|
t = _mm_unpacklo_epi16(mul_lo, mul_hi); \
|
|
accum = _mm_add_epi32(accum, t); \
|
|
t = _mm_unpackhi_epi16(mul_lo, mul_hi); \
|
|
accum = _mm_add_epi32(accum, t)
|
|
|
|
ITERATION(src_data[0] + start, accum0);
|
|
ITERATION(src_data[1] + start, accum1);
|
|
ITERATION(src_data[2] + start, accum2);
|
|
ITERATION(src_data[3] + start, accum3);
|
|
|
|
start += 16;
|
|
filter_values += 4;
|
|
}
|
|
|
|
int r = filter_length & 3;
|
|
if (r) {
|
|
// Note: filter_values must be padded to align_up(filter_offset, 8);
|
|
__m128i coeff;
|
|
coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
|
|
// Mask out extra filter taps.
|
|
coeff = _mm_and_si128(coeff, mask[r]);
|
|
|
|
__m128i coeff16lo = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
|
|
/* c1 c1 c1 c1 c0 c0 c0 c0 */
|
|
coeff16lo = _mm_unpacklo_epi16(coeff16lo, coeff16lo);
|
|
__m128i coeff16hi = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
|
|
coeff16hi = _mm_unpacklo_epi16(coeff16hi, coeff16hi);
|
|
|
|
__m128i src8, src16, mul_hi, mul_lo, t;
|
|
|
|
ITERATION(src_data[0] + start, accum0);
|
|
ITERATION(src_data[1] + start, accum1);
|
|
ITERATION(src_data[2] + start, accum2);
|
|
ITERATION(src_data[3] + start, accum3);
|
|
}
|
|
|
|
accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
|
|
accum0 = _mm_packs_epi32(accum0, zero);
|
|
accum0 = _mm_packus_epi16(accum0, zero);
|
|
accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
|
|
accum1 = _mm_packs_epi32(accum1, zero);
|
|
accum1 = _mm_packus_epi16(accum1, zero);
|
|
accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
|
|
accum2 = _mm_packs_epi32(accum2, zero);
|
|
accum2 = _mm_packus_epi16(accum2, zero);
|
|
accum3 = _mm_srai_epi32(accum3, ConvolutionFilter1D::kShiftBits);
|
|
accum3 = _mm_packs_epi32(accum3, zero);
|
|
accum3 = _mm_packus_epi16(accum3, zero);
|
|
|
|
*(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0);
|
|
*(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1);
|
|
*(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2);
|
|
*(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3);
|
|
|
|
out_row[0] += 4;
|
|
out_row[1] += 4;
|
|
out_row[2] += 4;
|
|
out_row[3] += 4;
|
|
}
|
|
#endif
|
|
}
|
|
|
|
// 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_SSE2(const ConvolutionFilter1D::Fixed* filter_values,
|
|
int filter_length,
|
|
unsigned char* const* source_data_rows,
|
|
int pixel_width,
|
|
unsigned char* out_row) {
|
|
#if defined(SIMD_SSE2)
|
|
int width = pixel_width & ~3;
|
|
|
|
__m128i zero = _mm_setzero_si128();
|
|
__m128i accum0, accum1, accum2, accum3, coeff16;
|
|
const __m128i* src;
|
|
// Output four pixels per iteration (16 bytes).
|
|
for (int out_x = 0; out_x < width; out_x += 4) {
|
|
|
|
// Accumulated result for each pixel. 32 bits per RGBA channel.
|
|
accum0 = _mm_setzero_si128();
|
|
accum1 = _mm_setzero_si128();
|
|
accum2 = _mm_setzero_si128();
|
|
accum3 = _mm_setzero_si128();
|
|
|
|
// Convolve with one filter coefficient per iteration.
|
|
for (int filter_y = 0; filter_y < filter_length; filter_y++) {
|
|
|
|
// Duplicate the filter coefficient 8 times.
|
|
// [16] cj cj cj cj cj cj cj cj
|
|
coeff16 = _mm_set1_epi16(filter_values[filter_y]);
|
|
|
|
// Load four pixels (16 bytes) together.
|
|
// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
|
|
src = reinterpret_cast<const __m128i*>(
|
|
&source_data_rows[filter_y][out_x << 2]);
|
|
__m128i src8 = _mm_loadu_si128(src);
|
|
|
|
// Unpack 1st and 2nd pixels from 8 bits to 16 bits for each channels =>
|
|
// multiply with current coefficient => accumulate the result.
|
|
// [16] a1 b1 g1 r1 a0 b0 g0 r0
|
|
__m128i src16 = _mm_unpacklo_epi8(src8, zero);
|
|
__m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
|
|
__m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
|
|
// [32] a0 b0 g0 r0
|
|
__m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
|
|
accum0 = _mm_add_epi32(accum0, t);
|
|
// [32] a1 b1 g1 r1
|
|
t = _mm_unpackhi_epi16(mul_lo, mul_hi);
|
|
accum1 = _mm_add_epi32(accum1, t);
|
|
|
|
// Unpack 3rd and 4th pixels from 8 bits to 16 bits for each channels =>
|
|
// multiply with current coefficient => accumulate the result.
|
|
// [16] a3 b3 g3 r3 a2 b2 g2 r2
|
|
src16 = _mm_unpackhi_epi8(src8, zero);
|
|
mul_hi = _mm_mulhi_epi16(src16, coeff16);
|
|
mul_lo = _mm_mullo_epi16(src16, coeff16);
|
|
// [32] a2 b2 g2 r2
|
|
t = _mm_unpacklo_epi16(mul_lo, mul_hi);
|
|
accum2 = _mm_add_epi32(accum2, t);
|
|
// [32] a3 b3 g3 r3
|
|
t = _mm_unpackhi_epi16(mul_lo, mul_hi);
|
|
accum3 = _mm_add_epi32(accum3, t);
|
|
}
|
|
|
|
// Shift right for fixed point implementation.
|
|
accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
|
|
accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
|
|
accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
|
|
accum3 = _mm_srai_epi32(accum3, ConvolutionFilter1D::kShiftBits);
|
|
|
|
// Packing 32 bits |accum| to 16 bits per channel (signed saturation).
|
|
// [16] a1 b1 g1 r1 a0 b0 g0 r0
|
|
accum0 = _mm_packs_epi32(accum0, accum1);
|
|
// [16] a3 b3 g3 r3 a2 b2 g2 r2
|
|
accum2 = _mm_packs_epi32(accum2, accum3);
|
|
|
|
// Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
|
|
// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
|
|
accum0 = _mm_packus_epi16(accum0, accum2);
|
|
|
|
if (has_alpha) {
|
|
// Compute the max(ri, gi, bi) for each pixel.
|
|
// [8] xx a3 b3 g3 xx a2 b2 g2 xx a1 b1 g1 xx a0 b0 g0
|
|
__m128i a = _mm_srli_epi32(accum0, 8);
|
|
// [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
|
|
__m128i b = _mm_max_epu8(a, accum0); // Max of r and g.
|
|
// [8] xx xx a3 b3 xx xx a2 b2 xx xx a1 b1 xx xx a0 b0
|
|
a = _mm_srli_epi32(accum0, 16);
|
|
// [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
|
|
b = _mm_max_epu8(a, b); // Max of r and g and b.
|
|
// [8] max3 00 00 00 max2 00 00 00 max1 00 00 00 max0 00 00 00
|
|
b = _mm_slli_epi32(b, 24);
|
|
|
|
// Make sure the value of alpha channel is always larger than maximum
|
|
// value of color channels.
|
|
accum0 = _mm_max_epu8(b, accum0);
|
|
} else {
|
|
// Set value of alpha channels to 0xFF.
|
|
__m128i mask = _mm_set1_epi32(0xff000000);
|
|
accum0 = _mm_or_si128(accum0, mask);
|
|
}
|
|
|
|
// Store the convolution result (16 bytes) and advance the pixel pointers.
|
|
_mm_storeu_si128(reinterpret_cast<__m128i*>(out_row), accum0);
|
|
out_row += 16;
|
|
}
|
|
|
|
// When the width of the output is not divisible by 4, We need to save one
|
|
// pixel (4 bytes) each time. And also the fourth pixel is always absent.
|
|
if (pixel_width & 3) {
|
|
accum0 = _mm_setzero_si128();
|
|
accum1 = _mm_setzero_si128();
|
|
accum2 = _mm_setzero_si128();
|
|
for (int filter_y = 0; filter_y < filter_length; ++filter_y) {
|
|
coeff16 = _mm_set1_epi16(filter_values[filter_y]);
|
|
// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
|
|
src = reinterpret_cast<const __m128i*>(
|
|
&source_data_rows[filter_y][width<<2]);
|
|
__m128i src8 = _mm_loadu_si128(src);
|
|
// [16] a1 b1 g1 r1 a0 b0 g0 r0
|
|
__m128i src16 = _mm_unpacklo_epi8(src8, zero);
|
|
__m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
|
|
__m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
|
|
// [32] a0 b0 g0 r0
|
|
__m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
|
|
accum0 = _mm_add_epi32(accum0, t);
|
|
// [32] a1 b1 g1 r1
|
|
t = _mm_unpackhi_epi16(mul_lo, mul_hi);
|
|
accum1 = _mm_add_epi32(accum1, t);
|
|
// [16] a3 b3 g3 r3 a2 b2 g2 r2
|
|
src16 = _mm_unpackhi_epi8(src8, zero);
|
|
mul_hi = _mm_mulhi_epi16(src16, coeff16);
|
|
mul_lo = _mm_mullo_epi16(src16, coeff16);
|
|
// [32] a2 b2 g2 r2
|
|
t = _mm_unpacklo_epi16(mul_lo, mul_hi);
|
|
accum2 = _mm_add_epi32(accum2, t);
|
|
}
|
|
|
|
accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
|
|
accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
|
|
accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
|
|
// [16] a1 b1 g1 r1 a0 b0 g0 r0
|
|
accum0 = _mm_packs_epi32(accum0, accum1);
|
|
// [16] a3 b3 g3 r3 a2 b2 g2 r2
|
|
accum2 = _mm_packs_epi32(accum2, zero);
|
|
// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
|
|
accum0 = _mm_packus_epi16(accum0, accum2);
|
|
if (has_alpha) {
|
|
// [8] xx a3 b3 g3 xx a2 b2 g2 xx a1 b1 g1 xx a0 b0 g0
|
|
__m128i a = _mm_srli_epi32(accum0, 8);
|
|
// [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
|
|
__m128i b = _mm_max_epu8(a, accum0); // Max of r and g.
|
|
// [8] xx xx a3 b3 xx xx a2 b2 xx xx a1 b1 xx xx a0 b0
|
|
a = _mm_srli_epi32(accum0, 16);
|
|
// [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
|
|
b = _mm_max_epu8(a, b); // Max of r and g and b.
|
|
// [8] max3 00 00 00 max2 00 00 00 max1 00 00 00 max0 00 00 00
|
|
b = _mm_slli_epi32(b, 24);
|
|
accum0 = _mm_max_epu8(b, accum0);
|
|
} else {
|
|
__m128i mask = _mm_set1_epi32(0xff000000);
|
|
accum0 = _mm_or_si128(accum0, mask);
|
|
}
|
|
|
|
for (int out_x = width; out_x < pixel_width; out_x++) {
|
|
*(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0);
|
|
accum0 = _mm_srli_si128(accum0, 4);
|
|
out_row += 4;
|
|
}
|
|
}
|
|
#endif
|
|
}
|
|
|
|
} // 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 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.length = filter_length;
|
|
filters_.push_back(instance);
|
|
|
|
max_filter_ = NS_MAX(max_filter_, filter_length);
|
|
}
|
|
|
|
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_sse2) {
|
|
#if !defined(SIMD_SSE2)
|
|
// Even we have runtime support for SSE2 instructions, since the binary
|
|
// was not built with SSE2 support, we had to fallback to C version.
|
|
use_sse2 = false;
|
|
#endif
|
|
|
|
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 + (use_sse2 ? 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;
|
|
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.
|
|
if (use_sse2) {
|
|
while (next_x_row < filter_offset + filter_length) {
|
|
if (next_x_row + 3 < last_filter_offset + last_filter_length - 1) {
|
|
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();
|
|
}
|
|
ConvolveHorizontally4_SSE2(src, filter_x, out_row);
|
|
next_x_row += 4;
|
|
} else {
|
|
// For the last row, SSE2 load possibly to access data beyond the
|
|
// image area. therefore we use C version here.
|
|
if (next_x_row == last_filter_offset + last_filter_length - 1) {
|
|
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());
|
|
}
|
|
} else {
|
|
ConvolveHorizontally_SSE2(
|
|
&source_data[next_x_row * source_byte_row_stride],
|
|
filter_x, row_buffer.AdvanceRow());
|
|
}
|
|
next_x_row++;
|
|
}
|
|
}
|
|
} else {
|
|
while (next_x_row < filter_offset + filter_length) {
|
|
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 (source_has_alpha) {
|
|
if (use_sse2) {
|
|
ConvolveVertically_SSE2<true>(filter_values, filter_length,
|
|
first_row_for_filter,
|
|
filter_x.num_values(), cur_output_row);
|
|
} else {
|
|
ConvolveVertically<true>(filter_values, filter_length,
|
|
first_row_for_filter,
|
|
filter_x.num_values(), cur_output_row);
|
|
}
|
|
} else {
|
|
if (use_sse2) {
|
|
ConvolveVertically_SSE2<false>(filter_values, filter_length,
|
|
first_row_for_filter,
|
|
filter_x.num_values(), cur_output_row);
|
|
} else {
|
|
ConvolveVertically<false>(filter_values, filter_length,
|
|
first_row_for_filter,
|
|
filter_x.num_values(), cur_output_row);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
} // namespace skia
|