SEEDS超像素分割算法的源码

ICA独立分量图像特征提取,内含源程序和图片，程序完整、易懂，有很好的参考价值。(The ICA independent component image feature extraction，Contains the source program and pictures, complete, and easy to understand and have a very good reference value. )

基于lsb的图像信息隐写算法 利用MATLAB实现(lsb-steganography)

斯坦福大学的姚邦鹏开发的一个图像分类算法，使用random forest实现了图像的精细区域描述，赢得了PASCAL VOC2011图像分类竞赛中的winner prize.经测试，程序完全可运行，且提供了MAC和Windows下的两种程序。(Image Classification: An Integration of Randomization and Discrimination in A Dense Feature Representation The goal of our method is to identify the discriminative fine-grained image region that distinguishes different classes. To achieve this goal we sample image regions from dense sampling space and use a random forest algorithm with discriminative classifier. Each node of the tree of random forest is trained and tested with fine-grained image patches combining the information from upstream nodes together. We implemented each node of the tree with a discriminative SVM classifier, which makes the node as a strong classifier. )

利用小波变换的去噪程序！和中值滤波进行对比！(The use of wavelet transform denoising procedure! And median filtering comparison!)

matlab实现灰度预测，很好的例子，有详细说明(Matlab to achieve grayscale prediction, a good example, with detailed instructions)

在MATLAB下的红外图像检测源码(In MATLAB under the infrared image detection source)

自适应直方图均衡算法的实现，即AHE算法，并提供样图进行对比。(Adaptive histogram equalization algorithm to achieve, namely AHE algorithm and provide comp image comparison.)

*****将picture内的所有文件拷贝到MATLAB7.1软件下的名为word的子文件夹下********** 1.testpipei_1.m文件为基于灰度的模板匹配代码，仅为单独使用，不具有交互性 2.testpipei_2.m文件为基于灰度的快速模板匹配代码，仅为单独使用，不具有交互性 3.three.m为带有界面的演示程序，包含了上述两种算法，在MATLAB7.1中，在命令窗口下输入 edit three （three文件一定要在work文件夹下）回车后就可以进行使用了。 4.testpipei_1.m和testpipei_2.m的函数使用说明详细见各自的文件内 5.testpipei_1.m,testpiei_2.m,getOrder.m,gettezheng.m都为函数文件 three.m和three.fig共同为演示界面文件。 (Using MATLAB to image matching two images)

vb仿大漠屏幕找图，速度极快 屏幕找色点 图像查找visualbasic vb6找图(VB,VB6,VISUAL BASICK ,FIND PICTURE ,QUICK SEARCH IMAGE.SEARCH PICTURE)

使用sift算法，找出图像的关键点，使用关键点作为匹配因子对两幅图像进行匹配，数据库中包含了丰富的可用图片库。(Use sift algorithm to find the image of the key points, key points to use as matching factor of two images match, the database contains a wealth of available gallery.)