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基于opencv的Kinect深度图像的去噪，滤波(Opencv based Kinect depth image denoising, filtering)

程序将界面与数据处理分开，界面采用MFC的对话框模板，对注册、训练、识别和主界面分别建立一个类，通过消息处理函数与用户进行交互，利用多线程来实时显示图像。 数据处理又分为了CFaceAlign（人脸检测+几何归一化）、CLightPrep（光照归一化）、CFaceFeature（Gabor特征提取）、CSubspace（计算Fisherface子空间）四个类，还有一个类 CFaceMngr 负责管理界面与数据之间的交流。这样的程序结构使对界面和算法彼此独立，互不影响。 每个类的具体方法请见相应头文件中的注释。(The program will interface with the data processing separate interface using MFC dialog template, registration, training, recognition and the main interface, respectively, to create a class that interacts with the user through a message handler, using multiple threads to display images in real time.   Data processing is divided into a CFaceAlign (Face Detection+ geometric normalization), CLightPrep (illumination normalization), CFaceFeature (Gabor feature extraction), CSubspace (computing Fisherface subspace) four categories, as well as a class is responsible for managing CFaceMngr interface and data exchange between. Such a program structure allows for interfaces and algorithms are independent of each other. Specific methods of each class, see the comments in the appropriate header files.)

这是bregman迭代的小例子，看完之后对图像处理的优化帮助很大，你可以掌握其中的优化算法，很好，很实用(This is the iterative Bregman small example, after reading on the optimization of image processing helps a lot, you can grasp optimization algorithm, which is very good, very practical.)

基于序贯蒙特卡罗方法的人体跟踪程序，对于学习蒙特卡罗粒子滤波器的人有重要参考价值。(Sequential Monte Carlo method based on human tracking procedures, Monte Carlo particle filter for learning a person has an important reference value.)

随着红外成像技术的发展，红外小目标检测在军事领域有越来越重要的应用。以此为背景，研究了天空、海面、大地等各种背景下红外视频中弱小目标的检测问题。 (With the development of infrared technology,dim small targets detection play a more and more important part in the military. The problem of dim small targets detecting in a infrared video with the background of the sky,the sea and the groundhas been studied. )

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.)

对于智能天线的设计仿真 包含有详细的说明,不错的源码(For the design of the smart antenna simulation contains detailed instructions, good source)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

说明：  基于开源计算机视觉库OpenCV的图像处理基于开源计算机视觉库OpenCV的图像处理(Based on open source computer vision library OpenCV image processing based on open source computer vision library OpenCV image processing)

利用Hough变换检测抛物线的算法。利用标准Hough变换从二值（黑白）图像中检测抛物线。(The use of parabolic Hough transform detection algorithms. Standard Hough transform from the binary (black and white) image in the detection of a parabola.)