MSR

基于高斯混合模型markov树算法的图像分割。。。(Gaussian mixture model based markov tree algorithm for image segmentation. . .)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

实现光流的代码，能够绘制光流的运动场。代码简单，无需配置，直接运行(It is Optical flow code.)

通过帧差追踪小车

本程序实现位图的读写，均衡化，滤波，LBP，LTP特征提取以及基于LBP，LTP和卡方距离，最近邻分类的人脸识别，批量给图片改名等功能(The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square distance, rename picture and some other functions.)

brox的光流算法第二部分，用于对两帧图像进行光流分析并检测运动物体(Brox optical flow algorithm of the second part, used in optical flow analysis was carried out on the two frames and detect moving objects)

说明：  图像处理算法质量评估，图像结构相似度（ssim)评价的matlab实现，并附带原始论文pdf(This is an implementation of the algorithm for calculating the Structural SIMilarity (SSIM) index between two images. Please refer to the following paper: Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error measurement to structural similarity" IEEE Transactios on Image Processing, vol. 13, no. 1, Jan. 2004.)

说明：  聚类分析作业，可以对图像根据颜色进行聚类分析，通道数可以自我选择，方便使用。(Clustering analysis can cluster images according to color, and the number of channels can be self-selected for easy use.)

VC做的图像处理方面的一些代码，仅供参考(VC do image processing of some code, only supplies the reference )

基于HIS空间的彩色烟雾图像分割算法，包含粗分，细分割与连通域提取(HIS color space based on image segmentation algorithm smoke contains coarse points, fine segmentation and connected domain extraction)