/* Copyright (c) 2012, Jan Schlicht Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. */ package resize import ( "image" "image/color" "math" ) // color.RGBA64 as array type rgba16 [4]uint16 // build RGBA from an arbitrary color func toRGBA(c color.Color) rgba16 { r, g, b, a := c.RGBA() return rgba16{uint16(r), uint16(g), uint16(b), uint16(a)} } func clampToUint16(x float32) (y uint16) { y = uint16(x) if x < 0 { y = 0 } else if x > float32(0xfffe) { y = 0xffff } return } type filterModel struct { src image.Image size int kernel func(float32) float32 tempRow []rgba16 tempCol []rgba16 } func (f *filterModel) convolution1d(x float32, p []rgba16) (c rgba16) { x -= float32(int(x)) m := float32(f.size/2 - 1) var k float32 var sum float32 = 0 l := [4]float32{0.0, 0.0, 0.0, 0.0} for j := range p { k = f.kernel(x + m - float32(j)) sum += k for i := range c { l[i] += float32(p[j][i]) * k } } for i := range c { c[i] = clampToUint16(l[i] / sum) } return } func (f *filterModel) Interpolate(x, y float32) color.RGBA64 { xf, yf := int(x)-f.size/2+1, int(y)-f.size/2+1 for i := 0; i < f.size; i++ { for j := 0; j < f.size; j++ { f.tempRow[j] = toRGBA(f.src.At(xf+j, yf+i)) } f.tempCol[i] = f.convolution1d(x, f.tempRow) } c := f.convolution1d(y, f.tempCol) return color.RGBA64{c[0], c[1], c[2], c[3]} } // Nearest-neighbor interpolation. // Approximates a value by returning the value of the nearest point. func NearestNeighbor(img image.Image) Filter { return &filterModel{img, 2, func(x float32) (y float32) { if x >= -0.5 && x < 0.5 { y = 1 } else { y = 0 } return }, make([]rgba16, 2), make([]rgba16, 2)} } // Bicubic interpolation func Bilinear(img image.Image) Filter { return &filterModel{img, 2, func(x float32) float32 { return 1 - float32(math.Abs(float64(x))) }, make([]rgba16, 2), make([]rgba16, 2)} } // Bicubic interpolation func Bicubic(img image.Image) Filter { return &filterModel{img, 4, func(x float32) (y float32) { absX := float32(math.Abs(float64(x))) if absX <= 1 { y = absX*absX*(1.5*absX-2.5) + 1 } else { y = absX*(absX*(2.5-0.5*absX)-4) + 2 } return }, make([]rgba16, 4), make([]rgba16, 4)} } // Lanczos interpolation (a=2). func Lanczos2(img image.Image) Filter { return &filterModel{img, 4, func(x float32) float32 { return float32(Sinc(float64(x))) * float32(Sinc(float64((x)/float32(2)))) }, make([]rgba16, 4), make([]rgba16, 4)} } // Lanczos interpolation (a=3). func Lanczos3(img image.Image) Filter { return &filterModel{img, 6, func(x float32) float32 { return float32(Sinc(float64(x))) * float32(Sinc(float64((x)/float32(3)))) }, make([]rgba16, 6), make([]rgba16, 6)} }