Image_Interpolation

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. )

利用MATLAB处理图形图像，求曲线的曲率(Using MATLAB processing graphics demand curve curvature)

用matlab做的基于小波降噪和自适应滤波的程序，已经调试可以使用。(Program based on wavelet noise reduction and adaptive filtering using matlab, debugging can use.)

利用改进的“参考白”算法对彩色图像进行光照补偿(Using improved "reference white" algorithm to compensate illumination of color image.)

基于PCA的人脸识别历程，包含PCA的算法，用MATLAB实现的。(face recognition based on PCA)

说明：  图像特征提取的Contourlet变换工具包，可以设置分解层次，例如，三层分解提取17维特征，用于纹理图像或者SAR图像分割应用中(Image feature extraction toolbox of Contourlet transform, you can set the level of decomposition, for example, three level with 17-dimensional, for the segmentation on texture image or SAR Image)

拉普拉斯算法的实现，程序是用vc++编写的(Laplasse algorithm)

基于肤色的图像分割，是用matlab实现的，希望大家有用(Image segmentation based on skin color is achieved with matlab, I hope it would be useful)

实现图像匹配，ssda算法，自主截图选择匹配位置(To achieve image matching, ssda algorithm, self-selection match position screenshots)

对两幅图像进行配准，分别提取两幅图像的surf特征点以及描述子，得到粗匹配结果，然后根据粗匹配结果，采用ransac方法计算基础矩阵，并去除误匹配点，得到较准确匹配结果(Two image registration, surf was extracted from the feature points in two images to get the coarse matching and descriptor, then according to the results, the coarse matching results, using RANSAC method to calculate the fundamental matrix, and eliminate the error matching, gain a more accurate matching results)