145 lines
3.6 KiB
Go
145 lines
3.6 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
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import (
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"image"
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"image/color"
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"math"
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)
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// color.RGBA64 as array
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type rgba16 [4]uint16
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// build rgba16 from an arbitrary color
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func toRgba16(c color.Color) rgba16 {
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r, g, b, a := c.RGBA()
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return rgba16{uint16(r), uint16(g), uint16(b), uint16(a)}
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}
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func clampToUint16(x float32) (y uint16) {
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y = uint16(x)
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if x < 0 {
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y = 0
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} else if x > float32(0xfffe) {
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y = 0xffff
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}
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return
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}
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type filterModel struct {
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src image.Image
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size int
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kernel func(float32) float32
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tempRow []rgba16
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tempCol []rgba16
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}
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func (f *filterModel) convolution1d(x float32, p []rgba16) (c rgba16) {
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var k float32
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var sum float32 = 0
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l := [4]float32{0.0, 0.0, 0.0, 0.0}
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for j := range p {
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k = f.kernel(x - float32(j))
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sum += k
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for i := range c {
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l[i] += float32(p[j][i]) * k
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}
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}
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for i := range c {
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c[i] = clampToUint16(l[i] / sum)
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}
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return
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}
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func (f *filterModel) Interpolate(x, y float32) color.RGBA64 {
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xf, yf := int(x)-f.size/2+1, int(y)-f.size/2+1
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x -= float32(xf)
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y -= float32(yf)
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for i := 0; i < f.size; i++ {
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for j := 0; j < f.size; j++ {
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f.tempRow[j] = toRgba16(f.src.At(xf+j, yf+i))
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}
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f.tempCol[i] = f.convolution1d(x, f.tempRow)
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}
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c := f.convolution1d(y, f.tempCol)
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return color.RGBA64{c[0], c[1], c[2], c[3]}
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}
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// Nearest-neighbor interpolation
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func NearestNeighbor(img image.Image) Filter {
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return &filterModel{img, 2, func(x float32) (y float32) {
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if x >= -0.5 && x < 0.5 {
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y = 1
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} else {
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y = 0
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}
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return
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}, make([]rgba16, 2), make([]rgba16, 2)}
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}
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// Bilinear interpolation
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func Bilinear(img image.Image) Filter {
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return &filterModel{img, 2, func(x float32) float32 {
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return 1 - float32(math.Abs(float64(x)))
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}, make([]rgba16, 2), make([]rgba16, 2)}
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}
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// Bicubic interpolation (with cubic hermite spline)
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func Bicubic(img image.Image) Filter {
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return &filterModel{img, 4, func(x float32) (y float32) {
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absX := float32(math.Abs(float64(x)))
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if absX <= 1 {
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y = absX*absX*(1.5*absX-2.5) + 1
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} else {
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y = absX*(absX*(2.5-0.5*absX)-4) + 2
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}
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return
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}, make([]rgba16, 4), make([]rgba16, 4)}
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}
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func MitchellNetravali(img image.Image) Filter {
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return &filterModel{img, 4, func(x float32) (y float32) {
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absX := float32(math.Abs(float64(x)))
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if absX <= 1 {
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y = absX*absX*(7*absX-12) + 16.0/3
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} else {
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y = -(absX - 2) * (absX - 2) / 3 * (7*absX - 8)
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}
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return
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}, make([]rgba16, 4), make([]rgba16, 4)}
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}
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func lanczosKernel(a uint) func(float32) float32 {
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return func(x float32) float32 {
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return float32(Sinc(float64(x))) * float32(Sinc(float64(x/float32(a))))
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}
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}
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// Lanczos interpolation (a=2).
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func Lanczos2(img image.Image) Filter {
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return &filterModel{img, 4, lanczosKernel(2), make([]rgba16, 4), make([]rgba16, 4)}
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}
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// Lanczos interpolation (a=3).
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func Lanczos3(img image.Image) Filter {
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return &filterModel{img, 6, lanczosKernel(3), make([]rgba16, 6), make([]rgba16, 6)}
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}
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