ISODATA

作者:J.Kittler and J.Illingworth KI阈值算法(Author：J.Kittler and J.Illingworth 1986)

读入图像，对图像进行预处理，随后检测边缘，对得到的图像进行二值化，然后进行hough变换，获得圆边界，将此图与原图叠加，增强边缘(Read in the image, the image pre-processing, followed by edge detection, binarization on the image to get, and then the hough transform to obtain the circular boundary, this map and the original image overlay to enhance the edge)

说明：  fast与sift算法结合，实现特征匹配，可以参考；fast与sift算法结合，实现特征匹配，可以参考(The combination of fast and sift algorithm can achieve feature matching, which can be referred to; the combination of fast and sift algorithm can achieve feature matching, which can be referred to)

说明：  KM算法，通过对图片的像素点特征分类，实现图片杂质检测等功能(KM algorithm, through the image of the pixel classification to achieve image impurity detection and other functions)

关于insar方面问题的处理方法，是一个有效的实例(InSAR aspects on the treatment method is an effective example of)

beta过程+稀疏表示，做单帧超分辨率重建(single imagle super-resolution by beta process)

用matlab对图像进行锐化，加噪，滤波，平滑滤波，中值滤波等处理(Matlab is used to sharpen the image, add noise, filter, smooth filter, median filter and so on)

说明：  区域生长算法，用于图像分割。 运行RunGrow.m 修改文件名即可。(Region growing algorithm for image segmentation. Run RunGrow.m modify the file name.)

PCA+Fisher人脸识别，已在ORL人脸库上测试，效果不错(face recognition,including PCA and Fisher methods.)

基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 (Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing)