gecko-dev/gfx/2d/image_operations.h

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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.
#ifndef SKIA_EXT_IMAGE_OPERATIONS_H_
#define SKIA_EXT_IMAGE_OPERATIONS_H_
#include "skia/include/core/SkTypes.h"
#include "Types.h"
#include "convolver.h"
#include "skia/include/core/SkRect.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);
};
// 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.
inline 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);
inline 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 (sinf(xpi) / xpi) * // sinc(x)
sinf(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)
inline 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 ((sinf(xpi) / xpi) * // sinc(x)
(0.54f + 0.46f * cosf(xpi / filter_size))); // hamming(x)
}
// ResizeFilter ----------------------------------------------------------------
// Encapsulates computation and storage of the filters required for one complete
// resize operation.
namespace resize {
// Returns the number of pixels that the filer spans, in filter space (the
// destination image).
inline float GetFilterSupport(ImageOperations::ResizeMethod method,
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(ImageOperations::ResizeMethod method,
int src_size, int dst_size,
int dest_subset_lo, int dest_subset_size,
ConvolutionFilter1D* output);
// Computes the filter value given the coordinate in filter space.
inline float ComputeFilter(ImageOperations::ResizeMethod method, 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;
}
}
}
} // namespace skia
#endif // SKIA_EXT_IMAGE_OPERATIONS_H_