gecko/gfx/2d/image_operations.cpp

561 lines
23 KiB
C++

// Copyright (c) 2006-2012 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 "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