Pemprosesan imej Golang: cara mewarna imbangan dan penyamaan histogram gambar

// 导入所需的包
import (
    "image"
    "image/color"
    "math"
)

// 颜色平衡函数
func balanceColors(img image.Image) image.Image {
    bounds := img.Bounds()
    width, height := bounds.Max.X, bounds.Max.Y

    // 创建一个新的RGBA图像
    balancedImg := image.NewRGBA(image.Rect(0, 0, width, height))

    rTotal, gTotal, bTotal := 0, 0, 0
    numPixels := width * height

    // 遍历图像的每一个像素
    for y := 0; y < height; y++ {
        for x := 0; x < width; x++ {
            // 获取像素的RGB值
            r, g, b, _ := img.At(x, y).RGBA()

            // 累加RGB值
            rTotal += int(r >> 8)
            gTotal += int(g >> 8)
            bTotal += int(b >> 8)
        }
    }

    // 计算平均RGB值
    rAvg := float64(rTotal) / float64(numPixels)
    gAvg := float64(gTotal) / float64(numPixels)
    bAvg := float64(bTotal) / float64(numPixels)

    // 遍历图像的每一个像素
    for y := 0; y < height; y++ {
        for x := 0; x < width; x++ {
            // 获取像素的RGB值
            r, g, b, a := img.At(x, y).RGBA()

            // 计算调整后的RGB值
            rBalanced := uint8(math.Min(float64(r>>8)*(rAvg/255), 255))
            gBalanced := uint8(math.Min(float64(g>>8)*(gAvg/255), 255))
            bBalanced := uint8(math.Min(float64(b>>8)*(bAvg/255), 255))

            // 设置新图像的像素值
            balancedImg.Set(x, y, color.RGBA{rBalanced, gBalanced, bBalanced, uint8(a>>8)})
        }
    }

    return balancedImg
}

// 导入所需的包
import (
    "image"
    "image/color"
    "math"
)

// 直方图均衡化函数
func equalizeHistogram(img image.Image) image.Image {
    bounds := img.Bounds()
    width, height := bounds.Max.X, bounds.Max.Y

    // 创建一个新的RGBA图像
    equalizedImg := image.NewRGBA(image.Rect(0, 0, width, height))

    // 计算像素值的累计分布
    var hist [256]int
    for y := 0; y < height; y++ {
        for x := 0; x < width; x++ {
            // 获取像素的灰度值
            r, g, b, _ := img.At(x, y).RGBA()
            gray := color.GrayModel.Convert(color.RGBA{uint8(r>>8), uint8(g>>8), uint8(b>>8), 0}).(color.Gray)

            // 累加灰度值分布
            hist[gray.Y]++
        }
    }

    // 计算像素值的累积直方图
    var cumHist [256]int
    cumHist[0] = hist[0]
    for i := 1; i < 256; i++ {
        cumHist[i] = cumHist[i-1] + hist[i]
    }

    // 计算像素值的映射关系
    var mapping [256]uint8
    for i := 0; i < 256; i++ {
        mapping[i] = uint8(math.Round(float64(cumHist[i]) * 255 / float64(width*height)))
    }

    // 遍历图像的每一个像素
    for y := 0; y < height; y++ {
        for x := 0; x < width; x++ {
            // 获取像素的灰度值
            r, g, b, a := img.At(x, y).RGBA()
            gray := color.GrayModel.Convert(color.RGBA{uint8(r>>8), uint8(g>>8), uint8(b>>8), uint8(a>>8)}).(color.Gray)

            // 获取映射后的灰度值
            newGray := mapping[gray.Y]

            // 设置新图像的像素值
            equalizedColor := color.Gray{newGray}
            equalizedImg.Set(x, y, equalizedColor)
        }
    }

    return equalizedImg
}