Win8Metro(C#)数字图像处理--2.10图像中值滤波

最新推荐文章于 2025-07-16 12:51:05 发布

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最新推荐文章于 2025-07-16 12:51:05 发布

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文章标签：人工智能 c#

原文链接：http://www.cnblogs.com/lonelyxmas/p/8553991.html

本文介绍了一种使用C#实现的Win8 Metro应用中的图像中值滤波处理方法。通过定义MedianFilterProcess函数，该函数接收WriteableBitmap类型的源图像，并返回经过中值滤波处理后的WriteableBitmap图像。此算法可以有效去除图像中的椒盐噪声。

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Win8Metro(C#)数字图像处理--2.10图像中值滤波

原文: Win8Metro(C#)数字图像处理--2.10图像中值滤波

[函数名称]

图像中值滤波函数MedianFilterProcess(WriteableBitmap src)

[函数代码]

///<summary>

/// Median filter process.

///</summary>

///<param name="src">Source image.</param>

///<returns></returns>

publicstaticWriteableBitmap MedianFilterProcess(WriteableBitmap src)////10中值滤波处理

{

if(src!=null )

{

int w = src.PixelWidth;

int h = src.PixelHeight;

WriteableBitmap filterImage =newWriteableBitmap(w, h);

byte[] temp = src.PixelBuffer.ToArray();

byte[] tempMask = (byte[])temp.Clone();

int v1 = 0, v2 = 0, v3 = 0, v4 = 0, v5 = 0, v6 = 0, v7 = 0, v8 = 0, t = 0;

for (int j = 1; j < h - 1; j++)

{

for (int i = 4; i < w * 4 - 4; i += 4)

{

v1 = (int)(temp[i - 4 + (j - 1) * w * 4] * 0.114 + temp[i - 4 + 1 + (j - 1) * w * 4] * 0.587 + temp[i - 4 + 2 + (j - 1) * w * 4] * 0.299);

v2 = (int)(temp[i + (j - 1) * w * 4] * 0.114 + temp[i + 1 + (j - 1) * w * 4] * 0.587 + temp[i + 2 + (j - 1) * w * 4] * 0.299);

v3 = (int)(temp[i + 4 + (j - 1) * w * 4] * 0.114 + temp[i + 4 + 1 + (j - 1) * w * 4] * 0.587 + temp[i + 4 + 2 + (j - 1) * w * 4] * 0.299);

v4 = (int)(temp[i - 4 + j * w * 4] * 0.114 + temp[i - 4 + 1 + j * w * 4] * 0.587 + temp[i - 4 + 2 + j * w * 4] * 0.299);

v5 = (int)(temp[i + 4 + j * w * 4] * 0.114 + temp[i + 4 + 1 + j * w * 4] * 0.587 + temp[i + 4 + 2 + j * w * 4] * 0.299);

v6 = (int)(temp[i - 4 + (j + 1) * w * 4] * 0.114 + temp[i - 4 + 1 + (j + 1) *w * 4] * 0.587 + temp[i - 4 + 2 + (j + 1) * w * 4] * 0.299);

v7 = (int)(temp[i + (j + 1) * w * 4] * 0.114 + temp[i + 1 + (j + 1) * w * 4] * 0.587 + temp[i + 2 + (j + 1) * w * 4] * 0.299);

v8 = (int)(temp[i + 4 + (j + 1) * w * 4] * 0.114 + temp[i + 4 + 1 + (j + 1) * w * 4] * 0.587 + temp[i + 4 + 2 + (j + 1) * w * 4] * 0.299);

t = GetMedianValue(v1, v2, v3, v4, v5, v6, v7, v8);

if(t==v1)

{

temp[i + j * w * 4] = (byte)tempMask[i - 4 + (j - 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i - 4 + 1 + (j - 1) * w * 4];

temp[i + 2 + j * w* 4] = (byte)tempMask[i - 4 + 2 + (j - 1) * w * 4];

}

elseif(t==v2)

{

temp[i + j * w * 4] = (byte)tempMask[i + (j - 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i + 1 + (j - 1) * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i + 2 + (j - 1) * w * 4];

}

elseif(t==v3)

{

temp[i + j * w * 4] = (byte)tempMask[i + 4 + (j - 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i + 1 + 4 + (j - 1) * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i + 2 + 4 + (j - 1) * w * 4];

}

elseif(t==v4)

{

temp[i + j * w * 4] = (byte)tempMask[i - 4 + j * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i - 4 + 1 + j * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i - 4 + 2 + j * w * 4];

}

elseif(t==v5)

{

temp[i + j * w * 4] = (byte)tempMask[i + 4 + j * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i + 4 + 1 + j * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i + 4 + 2 + j * w * 4];

}

elseif(t==v6)

{

temp[i + j * w * 4] = (byte)tempMask[i - 4 + (j + 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i - 4 + 1 + (j + 1) * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i - 4 + 2 + (j + 1) * w * 4];

}

elseif (t == v7)

{

temp[i + j * w * 4] = (byte)tempMask[i + (j + 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i + 1 + (j + 1) * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i + 2 + (j + 1) * w * 4];

}

else

{

temp[i + j * w * 4] = (byte)tempMask[i + 4 + (j + 1) * w * 4];

temp[i + 1 + j * w * 4] = (byte)tempMask[i + 4 + 1 + (j + 1) * w * 4];

temp[i + 2 + j * w * 4] = (byte)tempMask[i + 4 + 2 + (j + 1) * w * 4];

}

v1 = 0; v2 = 0; v3 = 0; v4 = 0; v5 = 0; v6 = 0; v7 = 0; v8 = 0; t = 0;

}

Stream sTemp = filterImage.PixelBuffer.AsStream();

sTemp.Seek(0,SeekOrigin.Begin);

sTemp.Write(temp, 0, w * 4 * h);

return filterImage;

}

else

{

returnnull;

}

privatestaticint GetMedianValue(paramsint[] src)

{

int w = src.Length;

int temp = src[0], m = 0;

for (int i = 1; i < (int)(w / 2); i++)

{

if (src[i] < temp)

{

m = src[i];

src[i] = temp;

temp = m;

}

else

continue;

}

return (int)((src[(int)(w / 2)] + src[(int)(-1 + w / 2)]) / 2);

}

posted on 2018-03-13 10:01 NET未来之路阅读( ...) 评论( ...) 编辑收藏

转载于:https://www.cnblogs.com/lonelyxmas/p/8553991.html