UCM

Visual C++ 6.0，基于opencv，MFC框架下开发，一个具有视频交互功能的桌面程序，功能类似于例程“Computer Vision Virtual Buttons”，能够实现基于视频交互的虚拟按钮的触发，(Visual C++ 6.0, based on opencv, MFC framework of development, a video interactive features of desktop applications, functions similar to the routine " Computer Vision Virtual Buttons" , to video-based interactive virtual button, trigger,)

guided_filter滤波器。对于图像处理方面有用。(filter. It is useful for image processing.)

利用遥感做变化检测的时候可以用到的数据。(Data Used in Change Detection Using Remote Sensing)

说明：  贝叶斯压缩感知例子 Bayesian Compressive Sensing, Shihao Ji, Ya Xue, and Lawrence Carin, IEEE Trans. Signal Processing, vol. 56, no. 6, June 2008.(Bayesian Compressive Sensing, Shihao Ji, Ya Xue, and Lawrence Carin, IEEE Trans. Signal Processing, vol. 56, no. 6, June 2008.)

对各种不同的传感器测得数据进行融合处理，从而获得精确的环境信息，能够做出更正确的判断。这个是一位非常优秀的老师的课件，非常值得一看！是关于数据融合方面的(On a variety of sensor data fusion measured to obtain accurate environmental information to make more accurate judgments. This is a very good teacher of the courseware, is worth a visit! Data fusion)

说明：  关于非下采样轮廓波域红外与可见光图像配准算法(On the registration algorithm of infrared and visible image in unsampled contour wave domain)

使用 RANSAC 算法计算仿射变换矩阵(RANSAC algorithm using an affine transformation matrix)

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

基于全变分（TV）的多光谱遥感图像恢复。当多光谱图像中一个通道模糊时，利用其它通道的图像特征辅助进行去模糊或反卷积，效果不错！！附带有对应的文章做参考。(This is a new image restoration or deconvolution method, which uses one of clear band image to constraint Total Variation de-blurring of degraded band image in multispectral image. It tested with different noise with different regularization parameters. It also compared with otherhods.)

说明：  结合模糊C均值聚类算法与水平集方法的图像分割代码，分割效果良好。(The image segmentation code based on fuzzy c-means clustering algorithm and level set method has a good segmentation effect.)