aw/go-resize
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Speedup calculation by exploiting the separability of the resizing filter.

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Should be ~5x faster! More optimization will follow.

before:
> go test -bench .
PASS
Benchmark_BigResizeLanczos3-4	       1	2438137093 ns/op
Benchmark_BigResizeLanczos3Lut-4	       1	1157612362 ns/op
Benchmark_Reduction-4	       2	 743950618 ns/op

after:
> go test -bench .
PASS
Benchmark_BigResizeLanczos3-4	       5	 403685685 ns/op
Benchmark_BigResizeLanczos3Lut-4	      10	 225539497 ns/op
Benchmark_Reduction-4	      10	 207004759 ns/op
This commit is contained in:
jst 2013-11-18 19:54:31 +01:00
parent 4d25061069
commit 494d8de4e5
2 changed files with 75 additions and 44 deletions
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56
filters.go
View File

@ -42,13 +42,13 @@ type filterModel struct {
// instead of blurring an image before downscaling to avoid aliasing,
// the filter is scaled by a factor which leads to a similar effect
factor [2]float32
factor float32
// for optimized access to image points
converter
// temporaries used by Interpolate
tempRow, tempCol []colorArray
// temporary used by Interpolate
tempRow []colorArray
}
func (f *filterModel) convolution1d(x float32, p []colorArray, factor float32) colorArray {
@ -72,20 +72,15 @@ func (f *filterModel) convolution1d(x float32, p []colorArray, factor float32) c
return c
}
func (f *filterModel) Interpolate(x, y float32) color.RGBA64 {
xf, yf := int(x)-len(f.tempRow)/2+1, int(y)-len(f.tempCol)/2+1
x -= float32(xf)
y -= float32(yf)
func (f *filterModel) Interpolate(u float32, y int) color.RGBA64 {
uf := int(u) - len(f.tempRow)/2 + 1
u -= float32(uf)
for i := range f.tempCol {
for j := range f.tempRow {
f.tempRow[j] = f.at(xf+j, yf+i)
}
f.tempCol[i] = f.convolution1d(x, f.tempRow, f.factor[0])
for i := range f.tempRow {
f.tempRow[i] = f.at(uf+i, y)
}
c := f.convolution1d(y, f.tempCol, f.factor[1])
c := f.convolution1d(u, f.tempRow, f.factor)
return color.RGBA64{
clampToUint16(c[0]),
clampToUint16(c[1]),
@ -96,46 +91,45 @@ func (f *filterModel) Interpolate(x, y float32) color.RGBA64 {
// createFilter tries to find an optimized converter for the given input image
// and initializes all filterModel members to their defaults
func createFilter(img image.Image, factor [2]float32, size int, kernel func(float32) float32) (f Filter) {
sizeX := size * (int(math.Ceil(float64(factor[0]))))
sizeY := size * (int(math.Ceil(float64(factor[1]))))
func createFilter(img image.Image, factor float32, size int, kernel func(float32) float32) (f Filter) {
sizeX := size * (int(math.Ceil(float64(factor))))
switch img.(type) {
default:
f = &filterModel{
kernel, factor,
&genericConverter{img},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
case *image.RGBA:
f = &filterModel{
kernel, factor,
&rgbaConverter{img.(*image.RGBA)},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
case *image.RGBA64:
f = &filterModel{
kernel, factor,
&rgba64Converter{img.(*image.RGBA64)},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
case *image.Gray:
f = &filterModel{
kernel, factor,
&grayConverter{img.(*image.Gray)},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
case *image.Gray16:
f = &filterModel{
kernel, factor,
&gray16Converter{img.(*image.Gray16)},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
case *image.YCbCr:
f = &filterModel{
kernel, factor,
&ycbcrConverter{img.(*image.YCbCr)},
make([]colorArray, sizeX), make([]colorArray, sizeY),
make([]colorArray, sizeX),
}
}
@ -172,7 +166,7 @@ func tableKernel(kernel func(float32) float32, tableSize int,
}
// Nearest-neighbor interpolation
func NearestNeighbor(img image.Image, factor [2]float32) Filter {
func NearestNeighbor(img image.Image, factor float32) Filter {
return createFilter(img, factor, 2, func(x float32) (y float32) {
if x >= -0.5 && x < 0.5 {
y = 1
@ -185,7 +179,7 @@ func NearestNeighbor(img image.Image, factor [2]float32) Filter {
}
// Bilinear interpolation
func Bilinear(img image.Image, factor [2]float32) Filter {
func Bilinear(img image.Image, factor float32) Filter {
return createFilter(img, factor, 2, func(x float32) (y float32) {
absX := float32(math.Abs(float64(x)))
if absX <= 1 {
@ -199,12 +193,12 @@ func Bilinear(img image.Image, factor [2]float32) Filter {
}
// Bicubic interpolation (with cubic hermite spline)
func Bicubic(img image.Image, factor [2]float32) Filter {
func Bicubic(img image.Image, factor float32) Filter {
return createFilter(img, factor, 4, splineKernel(0, 0.5))
}
// Mitchell-Netravali interpolation
func MitchellNetravali(img image.Image, factor [2]float32) Filter {
func MitchellNetravali(img image.Image, factor float32) Filter {
return createFilter(img, factor, 4, splineKernel(1.0/3.0, 1.0/3.0))
}
@ -245,25 +239,25 @@ func lanczosKernel(a uint) func(float32) float32 {
const lanczosTableSize = 300
// Lanczos interpolation (a=2)
func Lanczos2(img image.Image, factor [2]float32) Filter {
func Lanczos2(img image.Image, factor float32) Filter {
return createFilter(img, factor, 4, lanczosKernel(2))
}
// Lanczos interpolation (a=2) using a look-up table
// to speed up computation
func Lanczos2Lut(img image.Image, factor [2]float32) Filter {
func Lanczos2Lut(img image.Image, factor float32) Filter {
return createFilter(img, factor, 4,
tableKernel(lanczosKernel(2), lanczosTableSize, 2.0))
}
// Lanczos interpolation (a=3)
func Lanczos3(img image.Image, factor [2]float32) Filter {
func Lanczos3(img image.Image, factor float32) Filter {
return createFilter(img, factor, 6, lanczosKernel(3))
}
// Lanczos interpolation (a=3) using a look-up table
// to speed up computation
func Lanczos3Lut(img image.Image, factor [2]float32) Filter {
func Lanczos3Lut(img image.Image, factor float32) Filter {
return createFilter(img, factor, 6,
tableKernel(lanczosKernel(3), lanczosTableSize, 3.0))
}

63
resize.go
View File

@ -42,14 +42,14 @@ func (t *Trans2) Eval(x, y float32) (u, v float32) {
// Filter can interpolate at points (x,y)
type Filter interface {
Interpolate(x, y float32) color.RGBA64
Interpolate(u float32, y int) color.RGBA64
}
// InterpolationFunction return a Filter implementation
// that operates on an image. Two factors
// allow to scale the filter kernels in x- and y-direction
// to prevent moire patterns.
type InterpolationFunction func(image.Image, [2]float32) Filter
type InterpolationFunction func(image.Image, float32) Filter
// Resize an image to new width and height using the interpolation function interp.
// A new image with the given dimensions will be returned.
@ -64,24 +64,26 @@ func Resize(width, height uint, img image.Image, interp InterpolationFunction) i
scaleX, scaleY := calcFactors(width, height, oldWidth, oldHeight)
t := Trans2{scaleX, 0, float32(oldBounds.Min.X), 0, scaleY, float32(oldBounds.Min.Y)}
resizedImg := image.NewRGBA64(image.Rect(0, 0, int(0.7+oldWidth/scaleX), int(0.7+oldHeight/scaleY)))
//resizedImg := image.NewRGBA64(image.Rect(0, 0, int(0.7+oldWidth/scaleX), int(0.7+oldHeight/scaleY)))
resizedImg := image.NewRGBA64(image.Rect(0, 0, oldBounds.Dy(), int(0.7+oldWidth/scaleX)))
b := resizedImg.Bounds()
adjustX := 0.5 * ((oldWidth-1.0)/scaleX - float32(b.Dx()-1))
adjustY := 0.5 * ((oldHeight-1.0)/scaleY - float32(b.Dy()-1))
adjustX := 0.5 * ((oldWidth-1.0)/scaleX - float32(b.Dy()-1))
//adjustY := 0.5 * ((oldHeight-1.0)/scaleY - float32(b.Dy()-1))
n := numJobs(b.Dy())
c := make(chan int, n)
for i := 0; i < n; i++ {
go func(b image.Rectangle, c chan int) {
filter := interp(img, [2]float32{clampFactor(scaleX), clampFactor(scaleY)})
var u, v float32
filter := interp(img, float32(clampFactor(scaleX)))
var u float32
var color color.RGBA64
for y := b.Min.Y; y < b.Max.Y; y++ {
for x := b.Min.X; x < b.Max.X; x++ {
u, v = t.Eval(float32(x)+adjustX, float32(y)+adjustY)
color = filter.Interpolate(u, v)
for y := b.Min.X; y < b.Max.X; y++ {
for x := b.Min.Y; x < b.Max.Y; x++ {
u = t[0]*(float32(x)+adjustX) + t[2]
i := resizedImg.PixOffset(x, y)
color = filter.Interpolate(u, y)
i := resizedImg.PixOffset(y, x)
resizedImg.Pix[i+0] = uint8(color.R >> 8)
resizedImg.Pix[i+1] = uint8(color.R)
resizedImg.Pix[i+2] = uint8(color.G >> 8)
@ -100,7 +102,42 @@ func Resize(width, height uint, img image.Image, interp InterpolationFunction) i
<-c
}
return resizedImg
resultImg := image.NewRGBA64(image.Rect(0, 0, int(0.7+oldWidth/scaleX), int(0.7+oldHeight/scaleY)))
b = resultImg.Bounds()
adjustX = 0.5 * ((oldWidth-1.0)/scaleX - float32(b.Dx()-1))
for i := 0; i < n; i++ {
go func(b image.Rectangle, c chan int) {
filter := interp(resizedImg, float32(clampFactor(scaleY)))
var u float32
var color color.RGBA64
for y := b.Min.X; y < b.Max.X; y++ {
for x := b.Min.Y; x < b.Max.Y; x++ {
u = t[4]*(float32(x)+adjustX) + t[5]
color = filter.Interpolate(u, y)
i := resultImg.PixOffset(y, x)
resultImg.Pix[i+0] = uint8(color.R >> 8)
resultImg.Pix[i+1] = uint8(color.R)
resultImg.Pix[i+2] = uint8(color.G >> 8)
resultImg.Pix[i+3] = uint8(color.G)
resultImg.Pix[i+4] = uint8(color.B >> 8)
resultImg.Pix[i+5] = uint8(color.B)
resultImg.Pix[i+6] = uint8(color.A >> 8)
resultImg.Pix[i+7] = uint8(color.A)
}
}
c <- 1
}(image.Rect(b.Min.X, b.Min.Y+i*(b.Dy())/n, b.Max.X, b.Min.Y+(i+1)*(b.Dy())/n), c)
}
for i := 0; i < n; i++ {
<-c
}
return resultImg
}
// Calculate scaling factors using old and new image dimensions.