数字图像处理 使用C#进行图像处理八 Unsharp Masking

数字图像处理 使用C#进行图像处理八 Unsharp Masking

在数字图像处理中，Unsharp Masking是一种常用的图像增强技术。它通过增强图像的边缘和细节来提高图像的清晰度和锐度。本文将介绍如何使用C#编写代码实现Unsharp Masking算法，并附上部分代码示例和代码注释。

首先，我们需要导入System.Drawing命名空间，以便使用C#的图像处理功能。

csharp
using System.Drawing;

csharp
public static Bitmap UnsharpMasking(Bitmap image int radius double amount double threshold)
{
    // 创建一个与原始图像大小相同的空白图像
    Bitmap result = new Bitmap(image.Width image.Height);

    // 将原始图像转换为灰度图像
    Bitmap grayImage = Grayscale(image);

    // 创建一个高斯模糊滤波器
    GaussianBlurFilter blurFilter = new GaussianBlurFilter(radius);

    // 对灰度图像进行高斯模糊处理
    Bitmap blurredImage = blurFilter.Apply(grayImage);

    // 计算原始图像与模糊图像之间的差异
    Bitmap diffImage = Difference(blurredImage grayImage);

    // 对差异图像进行增强处理
    Bitmap enhancedImage = Enhance(diffImage amount threshold);

    // 将增强后的图像与原始图像相加得到最终结果
    for (int x = 0; x < image.Width; x++)
    {
        for (int y = 0; y < image.Height; y++)
        {
            Color originalColor = image.GetPixel(x y);
            Color enhancedColor = enhancedImage.GetPixel(x y);

            int red = originalColor.R + enhancedColor.R;
            int green = originalColor.G + enhancedColor.G;
            int blue = originalColor.B + enhancedColor.B;

            red = Math.Min(red 255);
            green = Math.Min(green 255);
            blue = Math.Min(blue 255);

            result.SetPixel(x y Color.FromArgb(red green blue));
        }
    }

    return result;
}

csharp
// 将彩色图像转换为灰度图像
public static Bitmap Grayscale(Bitmap image)
{
    Bitmap result = new Bitmap(image.Width image.Height);

    for (int x = 0; x < image.Width; x++)
    {
        for (int y = 0; y < image.Height; y++)
        {
            Color color = image.GetPixel(x y);
            int gray = (int)(color.R * 0.299 + color.G * 0.587 + color.B * 0.114);
            result.SetPixel(x y Color.FromArgb(gray gray gray));
        }
    }

    return result;
}

// 计算两个图像之间的差异
public static Bitmap Difference(Bitmap image1 Bitmap image2)
{
    Bitmap result = new Bitmap(image1.Width image1.Height);

    for (int x = 0; x < image1.Width; x++)
    {
        for (int y = 0; y < image1.Height; y++)
        {
            Color color1 = image1.GetPixel(x y);
            Color color2 = image2.GetPixel(x y);

            int diff = Math.Abs(color1.R - color2.R);

            result.SetPixel(x y Color.FromArgb(diff diff diff));
        }
    }

    return result;
}

// 对图像进行增强处理
public static Bitmap Enhance(Bitmap image double amount double threshold)
{
    Bitmap result = new Bitmap(image.Width image.Height);

    for (int x = 0; x < image.Width; x++)
    {
        for (int y = 0; y < image.Height; y++)
        {
            Color color = image.GetPixel(x y);

            if (color.R > threshold)
            {
                int enhanced = (int)(color.R * amount);
                enhanced = Math.Min(enhanced 255);
                result.SetPixel(x y Color.FromArgb(enhanced enhanced enhanced));
            }
            else
            {
                result.SetPixel(x y Color.FromArgb(color.R color.R color.R));
            }
        }
    }

    return result;
}

csharp
Bitmap image = new Bitmap(input.jpg);
Bitmap result = UnsharpMasking(image 5 1.5 20);
result.Save(output.jpg);