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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.)

这是SPAMS的原始代码，是稀疏表示的重要工具箱~(This is SPAMS original code, is an important toolbox sparse representation)

CT图像重建的几种ART迭代算法，包括一般的简单ART和联合ART。(Some kinds of ART iterations algorithm in CT reconstruction including simple ART and SART.)

用于图像去噪的代码，有模型去噪、双树复小波去噪，希望有帮助。(Code for image denoising, a denoising model dual tree complex wavelet denoising, hope to have help。)

提出了一种广义迭代收缩算法（GISA）非凸稀疏编码，可以解决稀疏编码的一些优化问题.希望能对大家有所帮助！(A generalized iterative contraction algorithm (GISA) is proposed to solve some of the optimization problems of sparse coding. We hope to be helpful to everyone!)

论文+ppt，我的数字图像处理课程设计，题目是基于均值滤波和小波分析的图像去噪方法(Thesis+ppt, digital image processing course design, subject image denoising method based on mean filter and wavelet analysis)

分形算法中的分形维数的源代码(Fractal dimension)

实例中的dotnetCHARTING.dll 文件即是 dotnetcharting控件，饼形图、柱形图等详见 核心代码部分 这是官方网址： http://www.dotnetcharting.com/

说明：  快速的人脸特征提取算法KPCA，比普通的pca特征提取算法在效率上好了不少(Fast facial feature extraction algorithm KPCA, than ordinary PCA feature extraction algorithm in the efficiency of a good many)

说明：  有注释的粒子滤波程序。粒子滤波(PF: Particle Filter)的思想基于蒙特卡洛方法(Monte Carlo methods)，它是利用粒子集来表示概率，可以用在任何形式的状态空间模型上。(Annotated particle filter program. Particle filter (PF: Particle Filter) Monte Carlo method based on the idea (Monte Carlo methods), which is set to represent the probability of a particle can be used in any form of state space model.)