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Bug 486918. Part 1: Import Chromium's higher-quality image scalers, since we know those to be good and shippable. r=jrmuizel

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This commit is contained in:
Joe Drew 2012-08-23 15:36:04 -04:00
parent 1827b6489f
commit b4317922d2
8 changed files with 1800 additions and 0 deletions
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1
gfx/2d/HelpersSkia.h
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@ -10,6 +10,7 @@
#include "skia/SkCanvas.h"
#include "skia/SkDashPathEffect.h"
#include "mozilla/Assertions.h"
#include <vector>
namespace mozilla {
namespace gfx {

10
gfx/2d/Makefile.in
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@ -29,6 +29,7 @@ EXPORTS_mozilla/gfx = \
Point.h \
Matrix.h \
Rect.h \
Scale.h \
Types.h \
Tools.h \
UserData.h \
@ -46,6 +47,7 @@ CPPSRCS = \
RecordedEvent.cpp \
DrawEventRecorder.cpp \
Blur.cpp \
Scale.cpp \
ScaledFontBase.cpp \
DrawTargetDual.cpp \
ImageScaling.cpp \
@ -76,6 +78,8 @@ CPPSRCS += \
SourceSurfaceSkia.cpp \
DrawTargetSkia.cpp \
PathSkia.cpp \
convolver.cpp \
image_operations.cpp \
$(NULL)
DEFINES += -DUSE_SKIA
@ -135,6 +139,12 @@ endif
endif
include $(topsrcdir)/config/rules.mk
include $(topsrcdir)/ipc/chromium/chromium-config.mk
# Due to bug 796023, we can't have -DUNICODE and -D_UNICODE; defining those
# macros changes the type of LOGFONT to LOGFONTW instead of LOGFONTA. This
# changes the symbol names of exported C++ functions that use LOGFONT.
DEFINES := $(filter-out -DUNICODE -D_UNICODE,$(DEFINES))
#ifeq ($(MOZ_WIDGET_TOOLKIT),cocoa)
#CPPSRCS += \

54
gfx/2d/Scale.cpp Normal file
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@ -0,0 +1,54 @@
/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
#include "Scale.h"
#ifdef USE_SKIA
#include "HelpersSkia.h"
#include "skia/SkBitmap.h"
#include "image_operations.h"
#endif
namespace mozilla {
namespace gfx {
bool Scale(uint8_t* srcData, int32_t srcWidth, int32_t srcHeight, int32_t srcStride,
uint8_t* dstData, int32_t dstWidth, int32_t dstHeight, int32_t dstStride,
SurfaceFormat format)
{
#ifdef USE_SKIA
bool opaque;
if (format == FORMAT_B8G8R8A8) {
opaque = false;
} else {
opaque = true;
}
SkBitmap::Config config = GfxFormatToSkiaConfig(format);
SkBitmap imgSrc;
imgSrc.setConfig(config, srcWidth, srcHeight, srcStride);
imgSrc.setPixels(srcData);
imgSrc.setIsOpaque(opaque);
// Rescaler is compatible with 32 bpp only. Convert to RGB32 if needed.
if (config != SkBitmap::kARGB_8888_Config) {
imgSrc.copyTo(&imgSrc, SkBitmap::kARGB_8888_Config);
}
// This returns an SkBitmap backed by dstData; since it also wrote to dstData,
// we don't need to look at that SkBitmap.
SkBitmap result = skia::ImageOperations::Resize(imgSrc,
skia::ImageOperations::RESIZE_BEST,
dstWidth, dstHeight,
dstData);
return result.readyToDraw();
#else
return false;
#endif
}
}
}

36
gfx/2d/Scale.h Normal file
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@ -0,0 +1,36 @@
/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
#ifndef MOZILLA_GFX_SCALE_H_
#define MOZILLA_GFX_SCALE_H_
#include "Types.h"
namespace mozilla {
namespace gfx {
/**
* Scale an image using a high-quality filter.
*
* Synchronously scales an image and writes the output to the destination in
* 32-bit format. The destination must be pre-allocated by the caller.
*
* Returns true if scaling was successful, and false otherwise. Currently, this
* function is implemented using Skia. If Skia is not enabled when building,
* calling this function will always return false.
*
* IMPLEMTATION NOTES:
* This API is not currently easily hardware acceleratable. A better API might
* take a SourceSurface and return a SourceSurface; the Direct2D backend, for
* example, could simply set a status bit on a copy of the image, and use
* Direct2D's high-quality scaler at draw time.
*/
GFX2D_API bool Scale(uint8_t* srcData, int32_t srcWidth, int32_t srcHeight, int32_t srcStride,
uint8_t* dstData, int32_t dstWidth, int32_t dstHeight, int32_t dstStride,
SurfaceFormat format);
}
}
#endif /* MOZILLA_GFX_BLUR_H_ */

864
gfx/2d/convolver.cpp Normal file
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@ -0,0 +1,864 @@
// Copyright (c) 2011 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "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
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>
void ConvolveHorizontally(const unsigned char* src_data,
const ConvolutionFilter1D& filter,
unsigned char* out_row) {
// Loop over each pixel on this row in the output image.
int num_values = filter.num_values();
for (int out_x = 0; out_x < num_values; out_x++) {
// Get the filter that determines the current output pixel.
int filter_offset, filter_length;
const ConvolutionFilter1D::Fixed* filter_values =
filter.FilterForValue(out_x, &filter_offset, &filter_length);
// Compute the first pixel in this row that the filter affects. It will
// touch |filter_length| pixels (4 bytes each) after this.
const unsigned char* row_to_filter = &src_data[filter_offset * 4];
// Apply the filter to the row to get the destination pixel in |accum|.
int accum[4] = {0};
for (int filter_x = 0; filter_x < filter_length; filter_x++) {
ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x];
accum[0] += cur_filter * row_to_filter[filter_x * 4 + 0];
accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1];
accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2];
if (has_alpha)
accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3];
}
// Bring this value back in range. All of the filter scaling factors
// are in fixed point with kShiftBits bits of fractional part.
accum[0] >>= ConvolutionFilter1D::kShiftBits;
accum[1] >>= ConvolutionFilter1D::kShiftBits;
accum[2] >>= ConvolutionFilter1D::kShiftBits;
if (has_alpha)
accum[3] >>= ConvolutionFilter1D::kShiftBits;
// Store the new pixel.
out_row[out_x * 4 + 0] = ClampTo8(accum[0]);
out_row[out_x * 4 + 1] = ClampTo8(accum[1]);
out_row[out_x * 4 + 2] = ClampTo8(accum[2]);
if (has_alpha)
out_row[out_x * 4 + 3] = ClampTo8(accum[3]);
}
}
// Does vertical convolution to produce one output row. The filter values and
// length are given in the first two parameters. These are applied to each
// of the rows pointed to in the |source_data_rows| array, with each row
// being |pixel_width| wide.
//
// The output must have room for |pixel_width * 4| bytes.
template<bool has_alpha>
void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
int filter_length,
unsigned char* const* source_data_rows,
int pixel_width,
unsigned char* out_row) {
// We go through each column in the output and do a vertical convolution,
// generating one output pixel each time.
for (int out_x = 0; out_x < pixel_width; out_x++) {
// Compute the number of bytes over in each row that the current column
// we're convolving starts at. The pixel will cover the next 4 bytes.
int byte_offset = out_x * 4;
// Apply the filter to one column of pixels.
int accum[4] = {0};
for (int filter_y = 0; filter_y < filter_length; filter_y++) {
ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y];
accum[0] += cur_filter * source_data_rows[filter_y][byte_offset + 0];
accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1];
accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2];
if (has_alpha)
accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3];
}
// Bring this value back in range. All of the filter scaling factors
// are in fixed point with kShiftBits bits of precision.
accum[0] >>= ConvolutionFilter1D::kShiftBits;
accum[1] >>= ConvolutionFilter1D::kShiftBits;
accum[2] >>= ConvolutionFilter1D::kShiftBits;
if (has_alpha)
accum[3] >>= ConvolutionFilter1D::kShiftBits;
// Store the new pixel.
out_row[byte_offset + 0] = ClampTo8(accum[0]);
out_row[byte_offset + 1] = ClampTo8(accum[1]);
out_row[byte_offset + 2] = ClampTo8(accum[2]);
if (has_alpha) {
unsigned char alpha = ClampTo8(accum[3]);
// Make sure the alpha channel doesn't come out smaller than any of the
// color channels. We use premultipled alpha channels, so this should
// never happen, but rounding errors will cause this from time to time.
// These "impossible" colors will cause overflows (and hence random pixel
// values) when the resulting bitmap is drawn to the screen.
//
// We only need to do this when generating the final output row (here).
int max_color_channel = NS_MAX(out_row[byte_offset + 0],
NS_MAX(out_row[byte_offset + 1], out_row[byte_offset + 2]));
if (alpha < max_color_channel)
out_row[byte_offset + 3] = max_color_channel;
else
out_row[byte_offset + 3] = alpha;
} else {
// No alpha channel, the image is opaque.
out_row[byte_offset + 3] = 0xff;
}
}
}
// 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_ = 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

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// 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 "prtypes.h"
#include "base/cpu.h"
#include "skia/SkTypes.h"
// 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 };
ConvolutionFilter1D();
~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.
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.length;
if (filter.length == 0) {
return NULL;
}
return &filter_values_[filter.data_location];
}
inline void PaddingForSIMD(int padding_count) {
// 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.
for (int i = 0; i < padding_count; ++i)
filter_values_.push_back(static_cast<Fixed>(0));
}
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 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).
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_sse2);
} // namespace skia
#endif // SKIA_EXT_CONVOLVER_H_

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// 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.
#include "base/basictypes.h"
#define _USE_MATH_DEFINES
#include <algorithm>
#include <cmath>
#include <limits>
#include "image_operations.h"
#include "nsAlgorithm.h"
#include "base/stack_container.h"
#include "convolver.h"
#include "skia/SkColorPriv.h"
#include "skia/SkBitmap.h"
#include "skia/SkRect.h"
#include "skia/SkFontHost.h"
namespace skia {
namespace {
// Returns the ceiling/floor as an integer.
inline int CeilInt(float val) {
return static_cast<int>(ceil(val));
}
inline int FloorInt(float val) {
return static_cast<int>(floor(val));
}
// Filter function computation -------------------------------------------------
// Evaluates the box filter, which goes from -0.5 to +0.5.
float EvalBox(float x) {
return (x >= -0.5f && x < 0.5f) ? 1.0f : 0.0f;
}
// Evaluates the Lanczos filter of the given filter size window for the given
// position.
//
// |filter_size| is the width of the filter (the "window"), outside of which
// the value of the function is 0. Inside of the window, the value is the
// normalized sinc function:
// lanczos(x) = sinc(x) * sinc(x / filter_size);
// where
// sinc(x) = sin(pi*x) / (pi*x);
float EvalLanczos(int filter_size, float x) {
if (x <= -filter_size || x >= filter_size)
return 0.0f; // Outside of the window.
if (x > -std::numeric_limits<float>::epsilon() &&
x < std::numeric_limits<float>::epsilon())
return 1.0f; // Special case the discontinuity at the origin.
float xpi = x * static_cast<float>(M_PI);
return (sin(xpi) / xpi) * // sinc(x)
sin(xpi / filter_size) / (xpi / filter_size); // sinc(x/filter_size)
}
// Evaluates the Hamming filter of the given filter size window for the given
// position.
//
// The filter covers [-filter_size, +filter_size]. Outside of this window
// the value of the function is 0. Inside of the window, the value is sinus
// cardinal multiplied by a recentered Hamming function. The traditional
// Hamming formula for a window of size N and n ranging in [0, N-1] is:
// hamming(n) = 0.54 - 0.46 * cos(2 * pi * n / (N-1)))
// In our case we want the function centered for x == 0 and at its minimum
// on both ends of the window (x == +/- filter_size), hence the adjusted
// formula:
// hamming(x) = (0.54 -
// 0.46 * cos(2 * pi * (x - filter_size)/ (2 * filter_size)))
// = 0.54 - 0.46 * cos(pi * x / filter_size - pi)
// = 0.54 + 0.46 * cos(pi * x / filter_size)
float EvalHamming(int filter_size, float x) {
if (x <= -filter_size || x >= filter_size)
return 0.0f; // Outside of the window.
if (x > -std::numeric_limits<float>::epsilon() &&
x < std::numeric_limits<float>::epsilon())
return 1.0f; // Special case the sinc discontinuity at the origin.
const float xpi = x * static_cast<float>(M_PI);
return ((sin(xpi) / xpi) * // sinc(x)
(0.54f + 0.46f * cos(xpi / filter_size))); // hamming(x)
}
// ResizeFilter ----------------------------------------------------------------
// Encapsulates computation and storage of the filters required for one complete
// resize operation.
class ResizeFilter {
public:
ResizeFilter(ImageOperations::ResizeMethod method,
int src_full_width, int src_full_height,
int dest_width, int dest_height,
const SkIRect& dest_subset);
// Returns the filled filter values.
const ConvolutionFilter1D& x_filter() { return x_filter_; }
const ConvolutionFilter1D& y_filter() { return y_filter_; }
private:
// Returns the number of pixels that the filer spans, in filter space (the
// destination image).
float GetFilterSupport(float scale) {
switch (method_) {
case ImageOperations::RESIZE_BOX:
// The box filter just scales with the image scaling.
return 0.5f; // Only want one side of the filter = /2.
case ImageOperations::RESIZE_HAMMING1:
// The Hamming filter takes as much space in the source image in
// each direction as the size of the window = 1 for Hamming1.
return 1.0f;
case ImageOperations::RESIZE_LANCZOS2:
// The Lanczos filter takes as much space in the source image in
// each direction as the size of the window = 2 for Lanczos2.
return 2.0f;
case ImageOperations::RESIZE_LANCZOS3:
// The Lanczos filter takes as much space in the source image in
// each direction as the size of the window = 3 for Lanczos3.
return 3.0f;
default:
return 1.0f;
}
}
// Computes one set of filters either horizontally or vertically. The caller
// will specify the "min" and "max" rather than the bottom/top and
// right/bottom so that the same code can be re-used in each dimension.
//
// |src_depend_lo| and |src_depend_size| gives the range for the source
// depend rectangle (horizontally or vertically at the caller's discretion
// -- see above for what this means).
//
// Likewise, the range of destination values to compute and the scale factor
// for the transform is also specified.
void ComputeFilters(int src_size,
int dest_subset_lo, int dest_subset_size,
float scale, float src_support,
ConvolutionFilter1D* output);
// Computes the filter value given the coordinate in filter space.
inline float ComputeFilter(float pos) {
switch (method_) {
case ImageOperations::RESIZE_BOX:
return EvalBox(pos);
case ImageOperations::RESIZE_HAMMING1:
return EvalHamming(1, pos);
case ImageOperations::RESIZE_LANCZOS2:
return EvalLanczos(2, pos);
case ImageOperations::RESIZE_LANCZOS3:
return EvalLanczos(3, pos);
default:
return 0;
}
}
ImageOperations::ResizeMethod method_;
// Size of the filter support on one side only in the destination space.
// See GetFilterSupport.
float x_filter_support_;
float y_filter_support_;
// Subset of scaled destination bitmap to compute.
SkIRect out_bounds_;
ConvolutionFilter1D x_filter_;
ConvolutionFilter1D y_filter_;
DISALLOW_COPY_AND_ASSIGN(ResizeFilter);
};
ResizeFilter::ResizeFilter(ImageOperations::ResizeMethod method,
int src_full_width, int src_full_height,
int dest_width, int dest_height,
const SkIRect& dest_subset)
: method_(method),
out_bounds_(dest_subset) {
// method_ will only ever refer to an "algorithm method".
SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
(method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
float scale_x = static_cast<float>(dest_width) /
static_cast<float>(src_full_width);
float scale_y = static_cast<float>(dest_height) /
static_cast<float>(src_full_height);
x_filter_support_ = GetFilterSupport(scale_x);
y_filter_support_ = GetFilterSupport(scale_y);
// Support of the filter in source space.
float src_x_support = x_filter_support_ / scale_x;
float src_y_support = y_filter_support_ / scale_y;
ComputeFilters(src_full_width, dest_subset.fLeft, dest_subset.width(),
scale_x, src_x_support, &x_filter_);
ComputeFilters(src_full_height, dest_subset.fTop, dest_subset.height(),
scale_y, src_y_support, &y_filter_);
}
// TODO(egouriou): Take advantage of periods in the convolution.
// Practical resizing filters are periodic outside of the border area.
// For Lanczos, a scaling by a (reduced) factor of p/q (q pixels in the
// source become p pixels in the destination) will have a period of p.
// A nice consequence is a period of 1 when downscaling by an integral
// factor. Downscaling from typical display resolutions is also bound
// to produce interesting periods as those are chosen to have multiple
// small factors.
// Small periods reduce computational load and improve cache usage if
// the coefficients can be shared. For periods of 1 we can consider
// loading the factors only once outside the borders.
void ResizeFilter::ComputeFilters(int src_size,
int dest_subset_lo, int dest_subset_size,
float scale, float src_support,
ConvolutionFilter1D* output) {
int dest_subset_hi = dest_subset_lo + dest_subset_size; // [lo, hi)
// When we're doing a magnification, the scale will be larger than one. This
// means the destination pixels are much smaller than the source pixels, and
// that the range covered by the filter won't necessarily cover any source
// pixel boundaries. Therefore, we use these clamped values (max of 1) for
// some computations.
float clamped_scale = NS_MIN(1.0f, scale);
// Speed up the divisions below by turning them into multiplies.
float inv_scale = 1.0f / scale;
StackVector<float, 64> filter_values;
StackVector<int16_t, 64> fixed_filter_values;
// Loop over all pixels in the output range. We will generate one set of
// filter values for each one. Those values will tell us how to blend the
// source pixels to compute the destination pixel.
for (int dest_subset_i = dest_subset_lo; dest_subset_i < dest_subset_hi;
dest_subset_i++) {
// Reset the arrays. We don't declare them inside so they can re-use the
// same malloc-ed buffer.
filter_values->clear();
fixed_filter_values->clear();
// This is the pixel in the source directly under the pixel in the dest.
// Note that we base computations on the "center" of the pixels. To see
// why, observe that the destination pixel at coordinates (0, 0) in a 5.0x
// downscale should "cover" the pixels around the pixel with *its center*
// at coordinates (2.5, 2.5) in the source, not those around (0, 0).
// Hence we need to scale coordinates (0.5, 0.5), not (0, 0).
// TODO(evannier): this code is therefore incorrect and should read:
// float src_pixel = (static_cast<float>(dest_subset_i) + 0.5f) * inv_scale;
// I leave it incorrect, because changing it would require modifying
// the results for the webkit test, which I will do in a subsequent checkin.
float src_pixel = dest_subset_i * inv_scale;
// Compute the (inclusive) range of source pixels the filter covers.
int src_begin = NS_MAX(0, FloorInt(src_pixel - src_support));
int src_end = NS_MIN(src_size - 1, CeilInt(src_pixel + src_support));
// Compute the unnormalized filter value at each location of the source
// it covers.
float filter_sum = 0.0f; // Sub of the filter values for normalizing.
for (int cur_filter_pixel = src_begin; cur_filter_pixel <= src_end;
cur_filter_pixel++) {
// Distance from the center of the filter, this is the filter coordinate
// in source space. We also need to consider the center of the pixel
// when comparing distance against 'src_pixel'. In the 5x downscale
// example used above the distance from the center of the filter to
// the pixel with coordinates (2, 2) should be 0, because its center
// is at (2.5, 2.5).
// TODO(evannier): as above (in regards to the 0.5 pixel error),
// this code is incorrect, but is left it for the same reasons.
// float src_filter_dist =
// ((static_cast<float>(cur_filter_pixel) + 0.5f) - src_pixel);
float src_filter_dist = cur_filter_pixel - src_pixel;
// Since the filter really exists in dest space, map it there.
float dest_filter_dist = src_filter_dist * clamped_scale;
// Compute the filter value at that location.
float filter_value = ComputeFilter(dest_filter_dist);
filter_values->push_back(filter_value);
filter_sum += filter_value;
}
// The filter must be normalized so that we don't affect the brightness of
// the image. Convert to normalized fixed point.
int16_t fixed_sum = 0;
for (size_t i = 0; i < filter_values->size(); i++) {
int16_t cur_fixed = output->FloatToFixed(filter_values[i] / filter_sum);
fixed_sum += cur_fixed;
fixed_filter_values->push_back(cur_fixed);
}
// The conversion to fixed point will leave some rounding errors, which
// we add back in to avoid affecting the brightness of the image. We
// arbitrarily add this to the center of the filter array (this won't always
// be the center of the filter function since it could get clipped on the
// edges, but it doesn't matter enough to worry about that case).
int16_t leftovers = output->FloatToFixed(1.0f) - fixed_sum;
fixed_filter_values[fixed_filter_values->size() / 2] += leftovers;
// Now it's ready to go.
output->AddFilter(src_begin, &fixed_filter_values[0],
static_cast<int>(fixed_filter_values->size()));
}
output->PaddingForSIMD(8);
}
ImageOperations::ResizeMethod ResizeMethodToAlgorithmMethod(
ImageOperations::ResizeMethod method) {
// Convert any "Quality Method" into an "Algorithm Method"
if (method >= ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD &&
method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD) {
return method;
}
// The call to ImageOperationsGtv::Resize() above took care of
// GPU-acceleration in the cases where it is possible. So now we just
// pick the appropriate software method for each resize quality.
switch (method) {
// Users of RESIZE_GOOD are willing to trade a lot of quality to
// get speed, allowing the use of linear resampling to get hardware
// acceleration (SRB). Hence any of our "good" software filters
// will be acceptable, and we use the fastest one, Hamming-1.
case ImageOperations::RESIZE_GOOD:
// Users of RESIZE_BETTER are willing to trade some quality in order
// to improve performance, but are guaranteed not to devolve to a linear
// resampling. In visual tests we see that Hamming-1 is not as good as
// Lanczos-2, however it is about 40% faster and Lanczos-2 itself is
// about 30% faster than Lanczos-3. The use of Hamming-1 has been deemed
// an acceptable trade-off between quality and speed.
case ImageOperations::RESIZE_BETTER:
return ImageOperations::RESIZE_HAMMING1;
default:
return ImageOperations::RESIZE_LANCZOS3;
}
}
} // namespace
// Resize ----------------------------------------------------------------------
// static
SkBitmap ImageOperations::Resize(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
const SkIRect& dest_subset,
void* dest_pixels /* = nullptr */) {
if (method == ImageOperations::RESIZE_SUBPIXEL)
return ResizeSubpixel(source, dest_width, dest_height, dest_subset);
else
return ResizeBasic(source, method, dest_width, dest_height, dest_subset,
dest_pixels);
}
// static
SkBitmap ImageOperations::ResizeSubpixel(const SkBitmap& source,
int dest_width, int dest_height,
const SkIRect& dest_subset) {
// Currently only works on Linux/BSD because these are the only platforms
// where SkFontHost::GetSubpixelOrder is defined.
#if defined(XP_UNIX)
// Understand the display.
const SkFontHost::LCDOrder order = SkFontHost::GetSubpixelOrder();
const SkFontHost::LCDOrientation orientation =
SkFontHost::GetSubpixelOrientation();
// Decide on which dimension, if any, to deploy subpixel rendering.
int w = 1;
int h = 1;
switch (orientation) {
case SkFontHost::kHorizontal_LCDOrientation:
w = dest_width < source.width() ? 3 : 1;
break;
case SkFontHost::kVertical_LCDOrientation:
h = dest_height < source.height() ? 3 : 1;
break;
}
// Resize the image.
const int width = dest_width * w;
const int height = dest_height * h;
SkIRect subset = { dest_subset.fLeft, dest_subset.fTop,
dest_subset.fLeft + dest_subset.width() * w,
dest_subset.fTop + dest_subset.height() * h };
SkBitmap img = ResizeBasic(source, ImageOperations::RESIZE_LANCZOS3, width,
height, subset);
const int row_words = img.rowBytes() / 4;
if (w == 1 && h == 1)
return img;
// Render into subpixels.
SkBitmap result;
result.setConfig(SkBitmap::kARGB_8888_Config, dest_subset.width(),
dest_subset.height());
result.allocPixels();
if (!result.readyToDraw())
return img;
SkAutoLockPixels locker(img);
if (!img.readyToDraw())
return img;
uint32_t* src_row = img.getAddr32(0, 0);
uint32_t* dst_row = result.getAddr32(0, 0);
for (int y = 0; y < dest_subset.height(); y++) {
uint32_t* src = src_row;
uint32_t* dst = dst_row;
for (int x = 0; x < dest_subset.width(); x++, src += w, dst++) {
uint8_t r = 0, g = 0, b = 0, a = 0;
switch (order) {
case SkFontHost::kRGB_LCDOrder:
switch (orientation) {
case SkFontHost::kHorizontal_LCDOrientation:
r = SkGetPackedR32(src[0]);
g = SkGetPackedG32(src[1]);
b = SkGetPackedB32(src[2]);
a = SkGetPackedA32(src[1]);
break;
case SkFontHost::kVertical_LCDOrientation:
r = SkGetPackedR32(src[0 * row_words]);
g = SkGetPackedG32(src[1 * row_words]);
b = SkGetPackedB32(src[2 * row_words]);
a = SkGetPackedA32(src[1 * row_words]);
break;
}
break;
case SkFontHost::kBGR_LCDOrder:
switch (orientation) {
case SkFontHost::kHorizontal_LCDOrientation:
b = SkGetPackedB32(src[0]);
g = SkGetPackedG32(src[1]);
r = SkGetPackedR32(src[2]);
a = SkGetPackedA32(src[1]);
break;
case SkFontHost::kVertical_LCDOrientation:
b = SkGetPackedB32(src[0 * row_words]);
g = SkGetPackedG32(src[1 * row_words]);
r = SkGetPackedR32(src[2 * row_words]);
a = SkGetPackedA32(src[1 * row_words]);
break;
}
break;
case SkFontHost::kNONE_LCDOrder:
break;
}
// Premultiplied alpha is very fragile.
a = a > r ? a : r;
a = a > g ? a : g;
a = a > b ? a : b;
*dst = SkPackARGB32(a, r, g, b);
}
src_row += h * row_words;
dst_row += result.rowBytes() / 4;
}
result.setIsOpaque(img.isOpaque());
return result;
#else
return SkBitmap();
#endif // OS_POSIX && !OS_MACOSX && !defined(OS_ANDROID)
}
// static
SkBitmap ImageOperations::ResizeBasic(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
const SkIRect& dest_subset,
void* dest_pixels /* = nullptr */) {
// Ensure that the ResizeMethod enumeration is sound.
SkASSERT(((RESIZE_FIRST_QUALITY_METHOD <= method) &&
(method <= RESIZE_LAST_QUALITY_METHOD)) ||
((RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
(method <= RESIZE_LAST_ALGORITHM_METHOD)));
// If the size of source or destination is 0, i.e. 0x0, 0xN or Nx0, just
// return empty.
if (source.width() < 1 || source.height() < 1 ||
dest_width < 1 || dest_height < 1)
return SkBitmap();
method = ResizeMethodToAlgorithmMethod(method);
// Check that we deal with an "algorithm methods" from this point onward.
SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
(method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
SkAutoLockPixels locker(source);
if (!source.readyToDraw())
return SkBitmap();
ResizeFilter filter(method, source.width(), source.height(),
dest_width, dest_height, dest_subset);
// Get a source bitmap encompassing this touched area. We construct the
// offsets and row strides such that it looks like a new bitmap, while
// referring to the old data.
const uint8_t* source_subset =
reinterpret_cast<const uint8_t*>(source.getPixels());
// Convolve into the result.
SkBitmap result;
result.setConfig(SkBitmap::kARGB_8888_Config,
dest_subset.width(), dest_subset.height());
if (dest_pixels) {
result.setPixels(dest_pixels);
} else {
result.allocPixels();
}
if (!result.readyToDraw())
return SkBitmap();
BGRAConvolve2D(source_subset, static_cast<int>(source.rowBytes()),
!source.isOpaque(), filter.x_filter(), filter.y_filter(),
static_cast<int>(result.rowBytes()),
static_cast<unsigned char*>(result.getPixels()),
/* sse = */ false);
// Preserve the "opaque" flag for use as an optimization later.
result.setIsOpaque(source.isOpaque());
return result;
}
// static
SkBitmap ImageOperations::Resize(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
void* dest_pixels /* = nullptr */) {
SkIRect dest_subset = { 0, 0, dest_width, dest_height };
return Resize(source, method, dest_width, dest_height, dest_subset,
dest_pixels);
}
} // namespace skia

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// Copyright (c) 2011 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#ifndef SKIA_EXT_IMAGE_OPERATIONS_H_
#define SKIA_EXT_IMAGE_OPERATIONS_H_
#include "skia/SkTypes.h"
#include "Types.h"
class SkBitmap;
struct SkIRect;
namespace skia {
class ImageOperations {
public:
enum ResizeMethod {
//
// Quality Methods
//
// Those enumeration values express a desired quality/speed tradeoff.
// They are translated into an algorithm-specific method that depends
// on the capabilities (CPU, GPU) of the underlying platform.
// It is possible for all three methods to be mapped to the same
// algorithm on a given platform.
// Good quality resizing. Fastest resizing with acceptable visual quality.
// This is typically intended for use during interactive layouts
// where slower platforms may want to trade image quality for large
// increase in resizing performance.
//
// For example the resizing implementation may devolve to linear
// filtering if this enables GPU acceleration to be used.
//
// Note that the underlying resizing method may be determined
// on the fly based on the parameters for a given resize call.
// For example an implementation using a GPU-based linear filter
// in the common case may still use a higher-quality software-based
// filter in cases where using the GPU would actually be slower - due
// to too much latency - or impossible - due to image format or size
// constraints.
RESIZE_GOOD,
// Medium quality resizing. Close to high quality resizing (better
// than linear interpolation) with potentially some quality being
// traded-off for additional speed compared to RESIZE_BEST.
//
// This is intended, for example, for generation of large thumbnails
// (hundreds of pixels in each dimension) from large sources, where
// a linear filter would produce too many artifacts but where
// a RESIZE_HIGH might be too costly time-wise.
RESIZE_BETTER,
// High quality resizing. The algorithm is picked to favor image quality.
RESIZE_BEST,
//
// Algorithm-specific enumerations
//
// Box filter. This is a weighted average of all of the pixels touching
// the destination pixel. For enlargement, this is nearest neighbor.
//
// You probably don't want this, it is here for testing since it is easy to
// compute. Use RESIZE_LANCZOS3 instead.
RESIZE_BOX,
// 1-cycle Hamming filter. This is tall is the middle and falls off towards
// the window edges but without going to 0. This is about 40% faster than
// a 2-cycle Lanczos.
RESIZE_HAMMING1,
// 2-cycle Lanczos filter. This is tall in the middle, goes negative on
// each side, then returns to zero. Does not provide as good a frequency
// response as a 3-cycle Lanczos but is roughly 30% faster.
RESIZE_LANCZOS2,
// 3-cycle Lanczos filter. This is tall in the middle, goes negative on
// each side, then oscillates 2 more times. It gives nice sharp edges.
RESIZE_LANCZOS3,
// Lanczos filter + subpixel interpolation. If subpixel rendering is not
// appropriate we automatically fall back to Lanczos.
RESIZE_SUBPIXEL,
// enum aliases for first and last methods by algorithm or by quality.
RESIZE_FIRST_QUALITY_METHOD = RESIZE_GOOD,
RESIZE_LAST_QUALITY_METHOD = RESIZE_BEST,
RESIZE_FIRST_ALGORITHM_METHOD = RESIZE_BOX,
RESIZE_LAST_ALGORITHM_METHOD = RESIZE_SUBPIXEL,
};
// Resizes the given source bitmap using the specified resize method, so that
// the entire image is (dest_size) big. The dest_subset is the rectangle in
// this destination image that should actually be returned.
//
// The output image will be (dest_subset.width(), dest_subset.height()). This
// will save work if you do not need the entire bitmap.
//
// The destination subset must be smaller than the destination image.
static SkBitmap Resize(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
const SkIRect& dest_subset,
void* dest_pixels = nullptr);
// Alternate version for resizing and returning the entire bitmap rather than
// a subset.
static SkBitmap Resize(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
void* dest_pixels = nullptr);
private:
ImageOperations(); // Class for scoping only.
// Supports all methods except RESIZE_SUBPIXEL.
static SkBitmap ResizeBasic(const SkBitmap& source,
ResizeMethod method,
int dest_width, int dest_height,
const SkIRect& dest_subset,
void* dest_pixels = nullptr);
// Subpixel renderer.
static SkBitmap ResizeSubpixel(const SkBitmap& source,
int dest_width, int dest_height,
const SkIRect& dest_subset);
};
} // namespace skia
#endif // SKIA_EXT_IMAGE_OPERATIONS_H_