图像处理之直方图匹配

1、 直方图匹配，又称直方图规定化，即变换原图的直方图为规定的某种形式的直方图，从而使两幅图像具有类似的色调和反差。直方图匹配属于非线性点运算。      直方图规定化的原理：对两个直方图都做均衡化，变成相同的归一化的均匀直方图，以此均匀直方图为媒介，再对参考图像做均衡化的逆运算 / <summary> / 直方图匹配 / </summary> / <param name="srcBmp">原始图像</param> / <param name="

2、matchingBmp">匹配图像</param> / <param name="dstBmp">处理后图像</param> / <returns>处理成功 true 失败 false</returns> public static bool HistogramMatching(Bitmap srcBmp, Bitmap matchingBmp, out Bitmap dstBmp) if (srcBmp = null | matchingBmp = null) dstBmp = null; ret

3、urn false; dstBmp = new Bitmap(srcBmp); Bitmap tempSrcBmp = new Bitmap(srcBmp); Bitmap tempMatchingBmp = new Bitmap(matchingBmp); double srcCpR = null; double srcCpG = null; double srcCpB = null; double matchCpB = null; double matchCpG = null; double matchCpR = null; /分别计算两幅图像的累计概率分布 getCumulativePr

4、obabilityRGB(tempSrcBmp, out srcCpR, out srcCpG, out srcCpB); getCumulativeProbabilityRGB(tempMatchingBmp, out matchCpR, out matchCpG, out matchCpB); double diffAR = 0, diffBR = 0, diffAG = 0, diffBG = 0, diffAB = 0, diffBB = 0; byte kR = 0, kG = 0, kB = 0; /逆映射函数 byte mapPixelR = new byte256; byte

5、mapPixelG = new byte256; byte mapPixelB = new byte256; /分别计算RGB三个分量的逆映射函数 /R for (int i = 0; i < 256; i+) diffBR = 1; for (int j = kR; j < 256; j+) /找到两个累计分布函数中最相似的位置 diffAR = Math.Abs(srcCpRi - matchCpRj); if (diffAR - diffBR < 1.0E-08) /当两概率之差小于0.000000001时可近似认为相等 diffBR = diffAR; /记录下此时的

6、灰度级 kR = (byte)j; else kR = (byte)Math.Abs(j - 1); break; if (kR = 255) for (int l = i; l < 256; l+) mapPixelRl = kR; break; mapPixelRi = kR; /G for (int i = 0; i < 256; i+) diffBG = 1; for (int j = kG; j < 256; j+) diffAG = Math.Abs(srcCpGi - matchCpGj); if (diffAG - diffBG < 1.0E-08) d

7、iffBG = diffAG; kG = (byte)j; else kG = (byte)Math.Abs(j - 1); break; if (kG = 255) for (int l = i; l < 256; l+) mapPixelGl = kG; break; mapPixelGi = kG; /B for (int i = 0; i < 256; i+) diffBB = 1; for (int j = kB; j < 256; j+) diffAB = Math.Abs(srcCpBi - matchCpBj); if (diffAB - diffBB <

8、; 1.0E-08) diffBB = diffAB; kB = (byte)j; else kB = (byte)Math.Abs(j - 1); break; if (kB = 255) for (int l = i; l < 256; l+) mapPixelBl = kB; break; mapPixelBi = kB; /映射变换 BitmapData bmpData = dstBmp.LockBits(new Rectangle(0, 0, dstBmp.Width, dstBmp.Height), ImageLockMode.ReadWrite, PixelFormat.F

9、ormat24bppRgb); unsafe byte* ptr = null; for (int i = 0; i < dstBmp.Height; i+) ptr = (byte*)bmpData.Scan0 + i * bmpData.Stride; for (int j = 0; j < dstBmp.Width; j+) ptrj * 3 + 2 = mapPixelRptrj * 3 + 2; ptrj * 3 + 1 = mapPixelGptrj * 3 + 1; ptrj * 3 = mapPixelBptrj * 3; dstBmp.UnlockBits(bmp

10、Data); return true; / <summary> / 计算各个图像分量的累计概率分布 / </summary> / <param name="srcBmp">原始图像</param> / <param name="cpR">R分量累计概率分布</param> / <param name="cpG">G分量累计概率分布</param> / <param name="cpB">B分量累计概率分布&l

11、t;/param> private static void getCumulativeProbabilityRGB(Bitmap srcBmp, out double cpR, out double cpG, out double cpB) if (srcBmp = null) cpB = cpG = cpR = null; return; cpR = new double256; cpG = new double256; cpB = new double256; int hR = null; int hG = null; int hB = null; double tempR = ne

12、w double256; double tempG = new double256; double tempB = new double256; getHistogramRGB(srcBmp, out hR, out hG, out hB); int totalPxl = srcBmp.Width * srcBmp.Height; for (int i = 0; i < 256; i+) if (i != 0) tempRi = tempRi - 1 + hRi; tempGi = tempGi - 1 + hGi; tempBi = tempBi - 1 + hBi; else tem

13、pR0 = hR0; tempG0 = hG0; tempB0 = hB0; cpRi = (tempRi / totalPxl); cpGi = (tempGi / totalPxl); cpBi = (tempBi / totalPxl); / <summary> / 获取图像三个分量的直方图数据 / </summary> / <param name="srcBmp">图像</param> / <param name="hR">R分量直方图数据</param> / <par

14、am name="hG">G分量直方图数据</param> / <param name="hB">B分量直方图数据</param> public static void getHistogramRGB(Bitmap srcBmp, out int hR, out int hG, out int hB) if (srcBmp = null) hR = hB = hG = null; return; hR = new int256; hB = new int256; hG = new int256; BitmapData bmpData = srcBmp.LockBits(new Rectangle(0, 0, srcBmp.Width, srcBmp.Height), ImageLockMode.ReadOnly, PixelFormat.Format24bppRgb); unsafe byte*