tif2raw

meanshift算法的python实现 + 图像化显示(meanshift with python)

说明：  实现matlab对感兴趣区域（ROI）提取(Implement MATLAB to extract ROI)

本程序实现灰度图像各向异性扩散(Anisotropic Diffusion)滤波算法，可以用于平滑信号，保留边缘，增强边缘对比度。与普通高斯Gaussian算法相比，它不会平滑边缘的图像。(The program implements grayscale image using anisotropic diffusion filtering algorithm.It can be used to smooth the signal, keep the edge, enhance the edge of the contrast. Compared with ordinary Gaussian algorithm, it does not smooth the image edges.)

水下图像增强方法，可以对退化的水下图像进行图像复原，但是对太模糊的水下图像不适用。(a method of underwater images enhancement)

基于Powell和互信息的多分辨率图像配准(Image registration Powell and mutual information)

背景减除的完整算法，《A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection》作者源代码(The "src" folder contains all of the source code. To run the program, follow these simple steps: 1. Start MATLAB and ensure the "src" folder is your current working directory. 2. Edit "bs.m" and "classify.m" so that the file paths point to the proper directories as specified. 3. In the MATLAB environment type "bs" which will train the background model from the sequence you specified in (2). 4. In the MATLAB environment type "classify" which will classify the sequence of images you specified in (2). 5. Now the classified images should be saved to disk in the folder you specified in (2).)

经典的跟踪算法，可以对人脸进行实时的跟踪。(Classical tracking algorithm can be real-time face tracking.)

基于C++MFC平台进行NDVI计算、最小距离分类、K均值分类，BP神经网络分类等以及精度评价(Based on C++MFC platform, NDVI computing, minimum distance classification, K mean classification, BP neural network classification and accuracy evaluation are carried out.)

实现了车辆目标的背景建模、前景检测、阴影消除、车辆跟踪(Achieve a vehicle target background modeling, foreground detection, shadow elimination, vehicle tracking)

说明：  利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)