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激光三维点云的处理源码，可以压缩点云，配准点云(Three-dimensional laser point cloud processing source code, can be compressed point cloud, point cloud registration)

图像拼接，用于实现多种格式，批处理遥感数据(Image mosaic, used to implement a variety of formats, batch processing of remote sensing data)

关于超分辨率图像恢复的凸集投影算法，运行结果正确。(code about super-resolution based on POCS)

信号压缩传感的实现(正交匹配追踪法Orthogonal Matching Pursuit)(The realization of signal compression sensing)

利用多线程技术把数据处理模块和图像显示模块分离，实现视频监控功能。(The use of multi-threading technology to data processing and image display module separation module for video monitoring.)

一款VC++图像开场加载效果，向大家演示了几种图像装载的特效实现的方法，比如扫描显示、滑动显示、渐入显示和马赛克显示等，大家在使用一些幻灯片软件的时候，经学会看到类似的效果，如果你有一定的VC++基础，你可以借鉴一下本效果的具体方法，再次扩展，可以制作出一款带特效的图像查看器(The opening loading effect of a VC++ image to demonstrate the effects achieved in several image loading, such as scanning, slide show, getting into the display and mosaic display, we learn to look at some slides software to similar effect, if you have certain VC++ basis, you can learn about the effects of specific methods, extended again, can create the image of a band effects Viewer)

纹理图像分割的算法和实例，其中包括理论的讲解和 MATLAB 文件。(Algorithms and Examples of Texture Image Segmentation)

用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法， 一个是getmapping,用以做算法的辅助函数， 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片， 具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

专门用于测试数码相机的分辨率使用,有实验用图(Specifically for use in testing digital camera resolution)

非常不错的IDL实现的放大缩小代码，希望能给大家带来方便(Achieved a very good zoom IDL code, I hope that it brings convenience)