dc93e1b98c
Fixes issue #31. The color value of every pixel of the resized image is created from the YCbCr colors of the input image. Therefore each of the three components have the same sample rate. This is the 4:4:4 chroma subsampling and the output images are now created accordingly.
615 lines
20 KiB
Go
615 lines
20 KiB
Go
/*
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Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
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Permission to use, copy, modify, and/or distribute this software for any purpose
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with or without fee is hereby granted, provided that the above copyright notice
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and this permission notice appear in all copies.
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THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
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REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
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FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
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INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
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OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
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TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
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THIS SOFTWARE.
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*/
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// Package resize implements various image resizing methods.
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//
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// The package works with the Image interface described in the image package.
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// Various interpolation methods are provided and multiple processors may be
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// utilized in the computations.
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//
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// Example:
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// imgResized := resize.Resize(1000, 0, imgOld, resize.MitchellNetravali)
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package resize
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import (
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"image"
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"runtime"
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"sync"
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)
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// An InterpolationFunction provides the parameters that describe an
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// interpolation kernel. It returns the number of samples to take
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// and the kernel function to use for sampling.
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type InterpolationFunction int
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// InterpolationFunction constants
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const (
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// Nearest-neighbor interpolation
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NearestNeighbor InterpolationFunction = iota
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// Bilinear interpolation
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Bilinear
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// Bicubic interpolation (with cubic hermite spline)
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Bicubic
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// Mitchell-Netravali interpolation
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MitchellNetravali
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// Lanczos interpolation (a=2)
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Lanczos2
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// Lanczos interpolation (a=3)
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Lanczos3
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)
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// kernal, returns an InterpolationFunctions taps and kernel.
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func (i InterpolationFunction) kernel() (int, func(float64) float64) {
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switch i {
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case Bilinear:
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return 2, linear
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case Bicubic:
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return 4, cubic
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case MitchellNetravali:
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return 4, mitchellnetravali
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case Lanczos2:
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return 4, lanczos2
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case Lanczos3:
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return 6, lanczos3
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default:
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// Default to NearestNeighbor.
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return 2, nearest
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}
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}
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// values <1 will sharpen the image
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var blur = 1.0
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// Resize scales an image to new width and height using the interpolation function interp.
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// A new image with the given dimensions will be returned.
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// If one of the parameters width or height is set to 0, its size will be calculated so that
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// the aspect ratio is that of the originating image.
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// The resizing algorithm uses channels for parallel computation.
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func Resize(width, height uint, img image.Image, interp InterpolationFunction) image.Image {
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scaleX, scaleY := calcFactors(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy()))
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if width == 0 {
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width = uint(0.7 + float64(img.Bounds().Dx())/scaleX)
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}
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if height == 0 {
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height = uint(0.7 + float64(img.Bounds().Dy())/scaleY)
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}
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// Trivial case: return input image
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if int(width) == img.Bounds().Dx() && int(height) == img.Bounds().Dy() {
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return img
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}
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if interp == NearestNeighbor {
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return resizeNearest(width, height, scaleX, scaleY, img, interp)
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}
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taps, kernel := interp.kernel()
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cpus := runtime.GOMAXPROCS(0)
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wg := sync.WaitGroup{}
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// Generic access to image.Image is slow in tight loops.
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// The optimal access has to be determined from the concrete image type.
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switch input := img.(type) {
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case *image.RGBA:
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// 8-bit precision
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temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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resizeRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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resizeNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA:
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// 8-bit precision
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temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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resizeNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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resizeNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.YCbCr:
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// 8-bit precision
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// accessing the YCbCr arrays in a tight loop is slow.
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// converting the image to ycc increases performance by 2x.
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temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
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result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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in := imageYCbCrToYCC(input)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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resizeYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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resizeYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result.YCbCr()
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case *image.RGBA64:
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// 16-bit precision
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temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA64:
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// 16-bit precision
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temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.Gray:
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// 8-bit precision
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temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.Gray)
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go func() {
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defer wg.Done()
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resizeGray(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.Gray)
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go func() {
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defer wg.Done()
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resizeGray(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.Gray16:
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// 16-bit precision
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temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.Gray16)
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go func() {
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defer wg.Done()
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resizeGray16(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.Gray16)
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go func() {
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defer wg.Done()
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resizeGray16(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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default:
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// 16-bit precision
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temp := image.NewNRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
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result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeGeneric(img, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA64)
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go func() {
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defer wg.Done()
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resizeNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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}
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}
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func resizeNearest(width, height uint, scaleX, scaleY float64, img image.Image, interp InterpolationFunction) image.Image {
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taps, _ := interp.kernel()
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cpus := runtime.GOMAXPROCS(0)
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wg := sync.WaitGroup{}
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switch input := img.(type) {
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case *image.RGBA:
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// 8-bit precision
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temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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nearestRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA:
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// 8-bit precision
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temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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nearestNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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nearestNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.YCbCr:
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// 8-bit precision
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// accessing the YCbCr arrays in a tight loop is slow.
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// converting the image to ycc increases performance by 2x.
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temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
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result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
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in := imageYCbCrToYCC(input)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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nearestYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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nearestYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result.YCbCr()
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case *image.RGBA64:
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// 16-bit precision
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temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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nearestRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.NRGBA64:
|
|
// 16-bit precision
|
|
temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.NRGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.Gray:
|
|
// 8-bit precision
|
|
temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.Gray)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.Gray)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.Gray16:
|
|
// 16-bit precision
|
|
temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.Gray16)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray16(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.Gray16)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray16(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
default:
|
|
// 16-bit precision
|
|
temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
|
|
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGeneric(img, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
}
|
|
|
|
}
|
|
|
|
// Calculates scaling factors using old and new image dimensions.
|
|
func calcFactors(width, height uint, oldWidth, oldHeight float64) (scaleX, scaleY float64) {
|
|
if width == 0 {
|
|
if height == 0 {
|
|
scaleX = 1.0
|
|
scaleY = 1.0
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
scaleX = scaleY
|
|
}
|
|
} else {
|
|
scaleX = oldWidth / float64(width)
|
|
if height == 0 {
|
|
scaleY = scaleX
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
}
|
|
}
|
|
return
|
|
}
|
|
|
|
type imageWithSubImage interface {
|
|
image.Image
|
|
SubImage(image.Rectangle) image.Image
|
|
}
|
|
|
|
func makeSlice(img imageWithSubImage, i, n int) image.Image {
|
|
return img.SubImage(image.Rect(img.Bounds().Min.X, img.Bounds().Min.Y+i*img.Bounds().Dy()/n, img.Bounds().Max.X, img.Bounds().Min.Y+(i+1)*img.Bounds().Dy()/n))
|
|
}
|