double-threshold-segmentation

基于贝叶斯最小错误率算法的崇明岛遥感图像分类程序。并且有饼状图显示各类地物比例(Minimum error rate based on Bayesian algorithm for Chongming Island, the remote sensing image classification procedures. And the pie chart below shows the proportion of various types of features)

基于IHS变换的图像融合matlab程序，基于IHS变换和小波帧变换的图像融合matlab程序。(IHS transform based image fusion matlab program, based on the IHS transform and wavelet frame transform matlab image fusion procedures.)

图像降噪、贝叶斯估计、盲源降噪,采用盲源方法进行噪声估计，再进行贝叶斯非局部均值降噪(Image denoising, Bias estimation and blind source noise，The blind source method for noise estimation, then the Bayes non local mean noise reduction)

采用MFC，实现遥感图像的基本增强，滤波，变换等功能。还可以保存数据。(Using MFC, to achieve the basic enhancement of remote sensing images, filtering, transformation and other functions. You can also save data)

Jianchao Yang的经典图像超分辨率程序(Classic image super-resolution process of professor Yang)

本文讲述了一种基于图像颜色直方图的图像相似度的度量的方法,。并用Matlab实现，有源代码(This article describes a method based on the image color histogram image similarity measure. And using Matlab, source code)

说明：  用Lorenz序列进行彩色图像加密，加密效果良好，性能得到较大提升(Using Lorenz sequence to encrypt color image, the encrypting effect is good and the performance is greatly improved.)

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. )

WAV音频的LSB信息隐藏，隐藏文件为二值图像，Matlab编程(WAV audio LSB information hiding, hidden files as binary image, Matlab programming)

这是一个视频图像处理的程序，通过混合高斯分布来建立背景模型，并且提取了运动目标，效果不错！(mixture of gaussians)