OCR

说明：  维纳滤波 最小二乘方 Lucy richardson图像复原 盲去卷积复原 图像复原法的综合比较(Wiener filtering least squares Lucy richardson image restoration blind deconvolution image restoration method to recover a comprehensive comparison)

三帧差分法，绝对可用，matlab实现，里面有视频和结果图。如果程序出错误，可用先把result.avi删除，在做测试、(Three difference method, absolutely free, matlab realize, there are videos and results map. If the program is an error that can be used to delete first result.avi while doing the test,)

说明：  二值化算法，含otsu,niblack,kapur,kittlerMet等方法(Binarization algorithm, including otsu, niblack, kapur, kittlerMet and other methods)

EM算法是最为经典的统计图像分割方法，代码基于matlab，使用EM算法实现图像分割,源代码加实例图像，非常好用(By using EM algrithm to realize the segementation of image)

说明：  一个基于块的纹理合成matlab源码程序(A block-based texture synthesis matlab source program)

此程序是关于图像分割技术，用分水岭和suan算子对细胞图像进行分割，并对细胞进行计数和统计。算出细胞个数和细胞面积。(This program is about image segmentation, watershed and suan operator with the cell image segmentation, and cell counting and statistics. Calculate the cell number and cell size.)

说明：  全变分去噪程序，用于图像去噪，该方法能克服图像去噪中的震荡效应，使图像更加光滑，并能保存边缘信息。(total variation denoisy)

moravec算子提取特征点，然后用相关度进行匹配(moravec operator feature point extraction, and then match the correlation)

数学形态学及相关算法的C语言实现实例 源代码调用OpenCV的cxcore和highgui两个库，应用C语言编写，实现对染色体图像中染色体数目的统计。代码中的核心算法为数学形态学的重要算法——开运算、闭运算（腐蚀和膨胀）。包含腐蚀处理、膨胀处理、自适应中值滤波、微分直方图法确定二值化阈值、种子填充算法等图像处理算法的C语言实现，值得参考。(Mathematical Morphology and related algorithms realize the C language source code examples of cxcore call OpenCV and highgui two libraries, the application of C language to realize pairs of chromosomes in the chromosome number of image statistics. The core algorithm code for an important mathematical morphology algorithms- open operation, closing operation (corrosion and expansion). Contains corrosion treatment, expansion of treatment, adaptive median filter, histogram method to determine differential binarization threshold, the seed fill algorithm, such as image processing algorithms realize the C language, it is also useful.)

非局部均值滤波 输入: 待平滑的图像 t: 搜索窗口半径 f: 相似性窗口半径 h: 平滑参数 NLmeans(ima,5,2,sigma) (Non-local mean filtering input: to be a smooth image t: the search window radius f: similarity of the window radius h: smoothing parameter NLmeans (ima, 5,2, sigma) )