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gecko/gfx/2d/convolver.cpp

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// Copyright (c) 2006-2011 The Chromium Authors. All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in
// the documentation and/or other materials provided with the
// distribution.
// * Neither the name of Google, Inc. nor the names of its contributors
// may be used to endorse or promote products derived from this
// software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
// FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
// COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
// BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
// OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
// AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
// OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
// OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
// SUCH DAMAGE.
#include "convolver.h"
#include <algorithm>
#include "nsAlgorithm.h"
#include "skia/SkTypes.h"
// note: SIMD_SSE2 is not enabled because of bugs, apparently
#if defined(SIMD_SSE2)
#include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h
#endif
#if defined(SK_CPU_LENDIAN)
#define R_OFFSET_IDX 0
#define G_OFFSET_IDX 1
#define B_OFFSET_IDX 2
#define A_OFFSET_IDX 3
#else
#define R_OFFSET_IDX 3
#define G_OFFSET_IDX 2
#define B_OFFSET_IDX 1
#define A_OFFSET_IDX 0
#endif
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;
}
// 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>
// This function is miscompiled with gcc 4.5 with pgo. See bug 827946.
#if defined(__GNUC__) && MOZ_GCC_VERSION_AT_LEAST(4, 5, 0) && !MOZ_GCC_VERSION_AT_LEAST(4, 6, 0)
__attribute__((optimize("-O1")))
#endif
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 + R_OFFSET_IDX];
accum[1] += cur_filter * row_to_filter[filter_x * 4 + G_OFFSET_IDX];
accum[2] += cur_filter * row_to_filter[filter_x * 4 + B_OFFSET_IDX];
if (has_alpha)
accum[3] += cur_filter * row_to_filter[filter_x * 4 + A_OFFSET_IDX];
}
// 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 + R_OFFSET_IDX] = ClampTo8(accum[0]);
out_row[out_x * 4 + G_OFFSET_IDX] = ClampTo8(accum[1]);
out_row[out_x * 4 + B_OFFSET_IDX] = ClampTo8(accum[2]);
if (has_alpha)
out_row[out_x * 4 + A_OFFSET_IDX] = 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 + R_OFFSET_IDX];
accum[1] += cur_filter
* source_data_rows[filter_y][byte_offset + G_OFFSET_IDX];
accum[2] += cur_filter
* source_data_rows[filter_y][byte_offset + B_OFFSET_IDX];
if (has_alpha)
accum[3] += cur_filter
* source_data_rows[filter_y][byte_offset + A_OFFSET_IDX];
}
// 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 + R_OFFSET_IDX] = ClampTo8(accum[0]);
out_row[byte_offset + G_OFFSET_IDX] = ClampTo8(accum[1]);
out_row[byte_offset + B_OFFSET_IDX] = 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 + R_OFFSET_IDX],
std::max(out_row[byte_offset + G_OFFSET_IDX], out_row[byte_offset + B_OFFSET_IDX]));
if (alpha < max_color_channel)
out_row[byte_offset + A_OFFSET_IDX] = max_color_channel;
else
out_row[byte_offset + A_OFFSET_IDX] = alpha;
} else {
// No alpha channel, the image is opaque.
out_row[byte_offset + A_OFFSET_IDX] = 0xff;
}
}
}
// Convolves horizontally along a single row. The row data is given in
// |src_data| and continues for the num_values() of the filter.
void ConvolveHorizontally_SSE2(const unsigned char* src_data,
const ConvolutionFilter1D& filter,
unsigned char* out_row) {
#if defined(SIMD_SSE2)
int num_values = filter.num_values();
int filter_offset, filter_length;
__m128i zero = _mm_setzero_si128();
__m128i mask[4];
// |mask| will be used to decimate all extra filter coefficients that are
// loaded by SIMD when |filter_length| is not divisible by 4.
// mask[0] is not used in following algorithm.
mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);
// Output one pixel each iteration, calculating all channels (RGBA) together.
for (int out_x = 0; out_x < num_values; out_x++) {
const ConvolutionFilter1D::Fixed* filter_values =
filter.FilterForValue(out_x, &filter_offset, &filter_length);
__m128i accum = _mm_setzero_si128();
// Compute the first pixel in this row that the filter affects. It will
// touch |filter_length| pixels (4 bytes each) after this.
const __m128i* row_to_filter =
reinterpret_cast<const __m128i*>(&src_data[filter_offset << 2]);
// We will load and accumulate with four coefficients per iteration.
for (int filter_x = 0; filter_x < filter_length >> 2; filter_x++) {
// Load 4 coefficients => duplicate 1st and 2nd of them for all channels.
__m128i coeff, coeff16;
// [16] xx xx xx xx c3 c2 c1 c0
coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
// [16] xx xx xx xx c1 c1 c0 c0
coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
// [16] c1 c1 c1 c1 c0 c0 c0 c0
coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
// Load four pixels => unpack the first two pixels to 16 bits =>
// multiply with coefficients => accumulate the convolution result.
// [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
__m128i src8 = _mm_loadu_si128(row_to_filter);
// [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*c0 b0*c0 g0*c0 r0*c0
__m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
accum = _mm_add_epi32(accum, t);
// [32] a1*c1 b1*c1 g1*c1 r1*c1
t = _mm_unpackhi_epi16(mul_lo, mul_hi);
accum = _mm_add_epi32(accum, t);
// Duplicate 3rd and 4th coefficients for all channels =>
// unpack the 3rd and 4th pixels to 16 bits => multiply with coefficients
// => accumulate the convolution results.
// [16] xx xx xx xx c3 c3 c2 c2
coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
// [16] c3 c3 c3 c3 c2 c2 c2 c2
coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
// [16] a3 g3 b3 r3 a2 g2 b2 r2
src16 = _mm_unpackhi_epi8(src8, zero);
mul_hi = _mm_mulhi_epi16(src16, coeff16);
mul_lo = _mm_mullo_epi16(src16, coeff16);
// [32] a2*c2 b2*c2 g2*c2 r2*c2
t = _mm_unpacklo_epi16(mul_lo, mul_hi);
accum = _mm_add_epi32(accum, t);
// [32] a3*c3 b3*c3 g3*c3 r3*c3
t = _mm_unpackhi_epi16(mul_lo, mul_hi);
accum = _mm_add_epi32(accum, t);
// Advance the pixel and coefficients pointers.
row_to_filter += 1;
filter_values += 4;
}
// When |filter_length| is not divisible by 4, we need to decimate some of
// the filter coefficient that was loaded incorrectly to zero; Other than
// that the algorithm is same with above, exceot that the 4th pixel will be
// always absent.
int r = filter_length&3;
if (r) {
// Note: filter_values must be padded to align_up(filter_offset, 8).
__m128i coeff, coeff16;
coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
// Mask out extra filter taps.
coeff = _mm_and_si128(coeff, mask[r]);
coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
// Note: line buffer must be padded to align_up(filter_offset, 16).
// We resolve this by use C-version for the last horizontal line.
__m128i src8 = _mm_loadu_si128(row_to_filter);
__m128i src16 = _mm_unpacklo_epi8(src8, zero);
__m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
__m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
__m128i 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);
coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
mul_hi = _mm_mulhi_epi16(src16, coeff16);
mul_lo = _mm_mullo_epi16(src16, coeff16);
t = _mm_unpacklo_epi16(mul_lo, mul_hi);
accum = _mm_add_epi32(accum, t);
}
// Shift right for fixed point implementation.
accum = _mm_srai_epi32(accum, ConvolutionFilter1D::kShiftBits);
// Packing 32 bits |accum| to 16 bits per channel (signed saturation).
accum = _mm_packs_epi32(accum, zero);
// Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
accum = _mm_packus_epi16(accum, zero);
// Store the pixel value of 32 bits.
*(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum);
out_row += 4;
}
#endif
}
// Convolves horizontally along four rows. The row data is given in
// |src_data| and continues for the num_values() of the filter.
// The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please
// refer to that function for detailed comments.
void ConvolveHorizontally4_SSE2(const unsigned char* src_data[4],
const ConvolutionFilter1D& filter,
unsigned char* out_row[4]) {
#if defined(SIMD_SSE2)
int num_values = filter.num_values();
int filter_offset, filter_length;
__m128i zero = _mm_setzero_si128();
__m128i mask[4];
// |mask| will be used to decimate all extra filter coefficients that are
// loaded by SIMD when |filter_length| is not divisible by 4.
// mask[0] is not used in following algorithm.
mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);
// Output one pixel each iteration, calculating all channels (RGBA) together.
for (int out_x = 0; out_x < num_values; out_x++) {
const ConvolutionFilter1D::Fixed* filter_values =
filter.FilterForValue(out_x, &filter_offset, &filter_length);
// four pixels in a column per iteration.
__m128i accum0 = _mm_setzero_si128();
__m128i accum1 = _mm_setzero_si128();
__m128i accum2 = _mm_setzero_si128();
__m128i accum3 = _mm_setzero_si128();
int start = (filter_offset<<2);
// We will load and accumulate with four coefficients per iteration.
for (int filter_x = 0; filter_x < (filter_length >> 2); filter_x++) {
__m128i coeff, coeff16lo, coeff16hi;
// [16] xx xx xx xx c3 c2 c1 c0
coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
// [16] xx xx xx xx c1 c1 c0 c0
coeff16lo = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
// [16] c1 c1 c1 c1 c0 c0 c0 c0
coeff16lo = _mm_unpacklo_epi16(coeff16lo, coeff16lo);
// [16] xx xx xx xx c3 c3 c2 c2
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_ = std::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
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