NCSA

对图像进行平滑处理，像各种滤波的方法，如均值滤波法、中值滤波法(Smoothing the image, like the various filtering methods, such as mean filtering, median filtering method)

基于spline的图像感兴趣区域提取，可用于基于区域的图像检索系统中。(spline- based region of interest image extraction, can be used for regional image retrieval system.)

支持向量机遥感图像分类代码，内含C、matlab代码，参考文献供学习(Support vector machine remote sensing image classification code )

说明：  基于距离变换的分水岭分割算法，该算法可以实现对粘连物体的分割。(Watershed algorithm)

用于求解张正友相机标定过程中的单应性矩阵(Homography matrix for camera calibration)

说明：  IFC文件格式读取和写出源码，目前该源码是1.0版本(IFC file format reads and writes the source code, which is currently version 1.0)

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

说明：  一种人脸识别方法,是利用眼睛虹膜进行识别(A face recognition method is the use of iris identification)

提取糖尿病视网膜病变眼底图像上硬性渗出。将彩色图像转为灰度图，对灰度图进行形态学处理、去背景、阈值分割，最终将原图上的硬性渗出区域用绿色标记出来。(this word is to extrac the hard exudates on diabetic retinopathy fundus image. The color image to grayscale on grayscale morphological processing to the background, threshold segmentation, ultimately on the original hard exudates area marked in green.)

自适应随机共振算法实现,具体内容注释中会有解释.(Adaptive stochastic resonance algorithm, the specific content of the Notes will be explained.)