/* 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 implements various image resizing methods. // // The package works with the Image interface described in the image package. // Various interpolation methods are provided and multiple processors may be // utilized in the computations. // // Example: // imgResized := resize.Resize(1000, 0, imgOld, resize.MitchellNetravali) package resize import ( "image" "runtime" "sync" ) // An InterpolationFunction provides the parameters that describe an // interpolation kernel. It returns the number of samples to take // and the kernel function to use for sampling. type InterpolationFunction int // InterpolationFunction constants const ( // Nearest-neighbor interpolation NearestNeighbor InterpolationFunction = iota // Bilinear interpolation Bilinear // Bicubic interpolation (with cubic hermite spline) Bicubic // Mitchell-Netravali interpolation MitchellNetravali // Lanczos interpolation (a=2) Lanczos2 // Lanczos interpolation (a=3) Lanczos3 ) // kernal, returns an InterpolationFunctions taps and kernel. func (i InterpolationFunction) kernel() (int, func(float64) float64) { switch i { case Bilinear: return 2, linear case Bicubic: return 4, cubic case MitchellNetravali: return 4, mitchellnetravali case Lanczos2: return 4, lanczos2 case Lanczos3: return 6, lanczos3 default: // Default to NearestNeighbor. return 2, nearest } } // values <1 will sharpen the image var blur = 1.0 // Resize scales an image to new width and height using the interpolation function interp. // A new image with the given dimensions will be returned. // If one of the parameters width or height is set to 0, its size will be calculated so that // the aspect ratio is that of the originating image. // The resizing algorithm uses channels for parallel computation. func Resize(width, height uint, img image.Image, interp InterpolationFunction) image.Image { scaleX, scaleY := calcFactors(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy())) if width == 0 { width = uint(0.7 + float64(img.Bounds().Dx())/scaleX) } if height == 0 { height = uint(0.7 + float64(img.Bounds().Dy())/scaleY) } if interp == NearestNeighbor { return resizeNearest(width, height, scaleX, scaleY, img, interp) } taps, kernel := interp.kernel() cpus := runtime.NumCPU() wg := sync.WaitGroup{} // Generic access to image.Image is slow in tight loops. // The optimal access has to be determined from the concrete image type. switch input := img.(type) { case *image.RGBA: // 8-bit precision temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width))) result := image.NewRGBA(image.Rect(0, 0, int(width), int(height))) // horizontal filter, results in transposed temporary image coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA) go func() { defer wg.Done() resizeRGBA(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA) go func() { defer wg.Done() resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength) }() } wg.Wait() return result case *image.YCbCr: // 8-bit precision // accessing the YCbCr arrays in a tight loop is slow. // converting the image before filtering will improve performance. inputAsRGBA := convertYCbCrToRGBA(input) temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width))) result := image.NewRGBA(image.Rect(0, 0, int(width), int(height))) // horizontal filter, results in transposed temporary image coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA) go func() { defer wg.Done() resizeRGBA(inputAsRGBA, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA) go func() { defer wg.Done() resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength) }() } wg.Wait() return result case *image.RGBA64: // 16-bit precision temp := image.NewRGBA64(image.Rect(0, 0, input.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 := createWeights16(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA64) go func() { defer wg.Done() resizeRGBA64(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA64) go func() { defer wg.Done() resizeGeneric(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 := createWeights8(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.Gray) go func() { defer wg.Done() resizeGray(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.Gray) go func() { defer wg.Done() resizeGray(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 := createWeights16(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.Gray16) go func() { defer wg.Done() resizeGray16(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.Gray16) go func() { defer wg.Done() resizeGray16(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 := createWeights16(temp.Bounds().Dy(), img.Bounds().Min.X, taps, blur, scaleX, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA64) go func() { defer wg.Done() resizeGeneric(img, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY, kernel) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA64) go func() { defer wg.Done() resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength) }() } wg.Wait() return result } } func resizeNearest(width, height uint, scaleX, scaleY float64, img image.Image, interp InterpolationFunction) image.Image { taps, _ := interp.kernel() cpus := runtime.NumCPU() wg := sync.WaitGroup{} switch input := img.(type) { case *image.RGBA: // 8-bit precision temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width))) result := image.NewRGBA(image.Rect(0, 0, int(width), int(height))) // horizontal filter, results in transposed temporary image coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA) go func() { defer wg.Done() nearestRGBA(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA) go func() { defer wg.Done() nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength) }() } wg.Wait() return result case *image.YCbCr: // 8-bit precision // accessing the YCbCr arrays in a tight loop is slow. // converting the image before filtering will improve performance. inputAsRGBA := convertYCbCrToRGBA(input) temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width))) result := image.NewRGBA(image.Rect(0, 0, int(width), int(height))) // horizontal filter, results in transposed temporary image coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), input.Bounds().Min.X, taps, blur, scaleX) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA) go func() { defer wg.Done() nearestRGBA(inputAsRGBA, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA) go func() { defer wg.Done() nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength) }() } wg.Wait() return result case *image.RGBA64: // 16-bit precision temp := image.NewRGBA64(image.Rect(0, 0, input.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(), input.Bounds().Min.X, taps, blur, scaleX) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(temp, i, cpus).(*image.RGBA64) go func() { defer wg.Done() nearestRGBA64(input, slice, scaleX, coeffs, offset, filterLength) }() } wg.Wait() // horizontal filter on transposed image, result is not transposed coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), temp.Bounds().Min.X, taps, blur, scaleY) wg.Add(cpus) for i := 0; i < cpus; i++ { slice := makeSlice(result, i, cpus).(*image.RGBA64) go func() { defer wg.Done() nearestGeneric(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(), input.Bounds().Min.X, 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(), temp.Bounds().Min.X, 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(), input.Bounds().Min.X, 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(), temp.Bounds().Min.X, 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(), img.Bounds().Min.X, 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(), temp.Bounds().Min.X, 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)) }