Golang은 이미지 제거 및 노이즈 처리 방법을 구현합니다.

package main

import (
    "fmt"
    "image"
    _ "image/jpeg"
    _ "image/png"
    "os"
)

func LoadImage(path string) (image.Image, error) {
    file, err := os.Open(path)
    if err != nil {
        return nil, err
    }
    defer file.Close()

    img, _, err := image.Decode(file)
    if err != nil {
        return nil, err
    }

    return img, nil
}

func main() {
    img, err := LoadImage("image.jpg")
    if err != nil {
        fmt.Println("Failed to load image:", err)
        return
    }

    fmt.Println("Loaded image successfully:", img.Bounds())
}

package main

import (
    "fmt"
    "github.com/disintegration/imaging"
    "image"
    "runtime"
)

func MedianFilter(img image.Image) image.Image {
    bounds := img.Bounds()
    width, height := bounds.Max.X, bounds.Max.Y

    // 创建一个新的图像，用于存储处理后的结果
    result := imaging.New(width, height, img.(*image.RGBA).Opaque)

    // 使用goroutine并行处理图像的每个像素点
    numCPU := runtime.NumCPU()
    ch := make(chan int, numCPU)
    done := make(chan bool)

    for i := 0; i < numCPU; i++ {
        go func() {
            for y := range ch {
                for x := 0; x < width; x++ {
                    // 取当前像素点周围的邻域像素点
                    neighbors := make([]uint8, 0)
                    for dy := -1; dy <= 1; dy++ {
                        for dx := -1; dx <= 1; dx++ {
                            if x+dx >= 0 && x+dx < width && y+dy >= 0 && y+dy < height {
                                r, _, _, _ := img.At(x+dx, y+dy).RGBA()
                                neighbors = append(neighbors, uint8(r>>8))
                            }
                        }
                    }

                    // 对邻域像素点进行排序，取中间值
                    imaging.QuickSortUint8(neighbors)

                    // 将中间值设为当前像素点的RGB值
                    r, _, _, a := img.At(x, y).RGBA()
                    result.Set(x, y, image.RGBA{
                        R: neighbors[len(neighbors)/2],
                        G: neighbors[len(neighbors)/2],
                        B: neighbors[len(neighbors)/2],
                        A: uint8(a >> 8),
                    })
                }
            }
            done <- true
        }()
    }

    for y := 0; y < height; y++ {
        ch <- y
    }
    close(ch)

    for i := 0; i < numCPU; i++ {
        <-done
    }

    return result
}

func main() {
    img, err := LoadImage("image.jpg")
    if err != nil {
        fmt.Println("Failed to load image:", err)
        return
    }

    filteredImg := MedianFilter(img)
    imaging.Save(filteredImg, "filtered_image.jpg")
    fmt.Println("Filtered image saved successfully!")
}