README
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# rescribe.xyz/integralimg package NOTE: This package has been renamed rescribe.xyz/integral - future updates will be there. Please update links. This package contains methods and structures for dealing with Integral Images, aka Summed Area Tables. These are structures which precompute the sum of pixels to the left and above each pixel, which can make several common image processing operations much faster. This is a Go package, and can be installed in the standard go way, by running `go get rescribe.xyz/integralimg` and documentation can be read with the `go doc` command or online at <https://pkg.go.dev/rescribe.xyz/integralimg>. ## Contributions Any and all comments, bug reports, patches or pull requests would be very welcomely received. Please email them to <nick@rescribe.xyz>. ## License This package is licensed under the GPLv3. See the LICENSE file for more details.
Documentation
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Overview ¶
NOTE: This package has been renamed rescribe.xyz/integral - future updates will be there. Please update links.
integralimg is a package for processing integral images, aka summed area tables. These are structures which precompute the sum of pixels to the left and above each pixel, which can make several common image processing operations much faster.
A lot of image processing operations rely on many calculations of the sum or mean of a set of pixels. As these have been precalculated for an integral Image, these calculations are much faster. Image.Sum() and Image.Mean() functions are provided by this package to take advantage of this.
Another common requirement is standard deviation over an area of an image. This can be calculated by creating an integral Image and squared integral Image (SqImage) for a base image, and passing them to the MeanStdDev() function provided.
Index ¶
Examples ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func MeanStdDev ¶ added in v0.3.0
MeanStdDev calculates the mean and standard deviation of a section of an image, using the corresponding regular and square integral images.
Example ¶
package main
import (
"fmt"
"image"
"image/draw"
"log"
"os"
_ "image/png"
"rescribe.xyz/integralimg"
)
func main() {
f, err := os.Open("testdata/in.png")
if err != nil {
log.Fatal(err)
}
defer f.Close()
img, _, err := image.Decode(f)
if err != nil {
log.Fatal(err)
}
b := img.Bounds()
integral := integralimg.NewImage(b)
sqIntegral := integralimg.NewSqImage(b)
draw.Draw(integral, b, img, b.Min, draw.Src)
draw.Draw(sqIntegral, b, img, b.Min, draw.Src)
mean, stddev := integralimg.MeanStdDev(*integral, *sqIntegral, b)
fmt.Printf("Mean: %f, Standard Deviation: %f\n", mean, stddev)
}
Output: Mean: 54677.229042, Standard Deviation: 21643.721672
Types ¶
type Image ¶ added in v0.2.0
type Image [][]uint64
Image is an integral Image
func NewImage ¶ added in v0.2.0
NewImage returns a new integral Image with the given bounds.
func (Image) Mean ¶ added in v0.3.0
Mean returns the average value of pixels in a section of an image
Example ¶
package main
import (
"fmt"
"image"
"image/draw"
"log"
"os"
_ "image/png"
"rescribe.xyz/integralimg"
)
func main() {
f, err := os.Open("testdata/in.png")
if err != nil {
log.Fatal(err)
}
defer f.Close()
img, _, err := image.Decode(f)
if err != nil {
log.Fatal(err)
}
b := img.Bounds()
integral := integralimg.NewImage(b)
draw.Draw(integral, b, img, b.Min, draw.Src)
fmt.Printf("Mean: %f\n", integral.Mean(b))
}
Output: Mean: 54677.229042
func (Image) Sum ¶ added in v0.3.0
Sum returns the sum of all pixels in a section of an image
Example ¶
package main
import (
"fmt"
"image"
"image/draw"
"log"
"os"
_ "image/png"
"rescribe.xyz/integralimg"
)
func main() {
f, err := os.Open("testdata/in.png")
if err != nil {
log.Fatal(err)
}
defer f.Close()
img, _, err := image.Decode(f)
if err != nil {
log.Fatal(err)
}
b := img.Bounds()
integral := integralimg.NewImage(b)
draw.Draw(integral, b, img, b.Min, draw.Src)
fmt.Printf("Sum: %d\n", integral.Sum(b))
}
Output: Sum: 601340165
type SqImage ¶ added in v0.2.0
type SqImage [][]uint64
SqImage is a Square integral Image. A squared integral image is an integral image for which the square of each pixel is saved; this is useful for efficiently calculating Standard Deviation.
func NewSqImage ¶ added in v0.2.0
NewSqImage returns a new squared integral Image with the given bounds.
func (SqImage) Mean ¶ added in v0.3.0
Mean returns the average value of pixels in a section of an image
Source Files