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图像处理PDF格式的讲义，个人感觉不错，希望对大家有所帮助！(image processing PDF format overhead, personal feeling good, and I hope to help you!)

利用小波变换进行图像去噪处理，包括各种软硬阈值的选取函数(Using Wavelet Transform for Image Denoising, including a variety of select hard and soft threshold function)

说明：  用于图像边缘检测，使用matlab检测图像边缘特征(For image edge detection, use matlab to detect image edge features)

用粒子滤波器实现的多运动员跟踪，包含了data文件(Using Particle Filters athletes realize the multi-tracking, contains a data file)

视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。( Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial This tutorial will demonstrate how Gabor transforms and generalized linear model (GLM) can be used for detection of retinal vessels in images. Specifically, we will attempt to detect the retinal vessels a training image , by first, convoluting multiple Gabor filters with the image. A GLM will be determined using the Gabor transformed images as features (the independent variables), and the locations of the vessels as the outcome (the dependent variable).)

此程序为袁晓彤CVPR论文“基于多任务联合稀疏表示的的视觉分类”的主代码部分(The program for Yuan Xiaotong CVPR paper " visual classification with Muti-task joint sparse representation" main code of the parts)

本书主要讲述如何使用Visual C++进行数字图像处理。全书对常用的数字图像处理算法进行了介绍。(This book focuses on how to use Visual C++ digital image processing. The book is commonly used digital image processing algorithms were introduced.)

基于SUFT的特征提取与匹配，内涵详细的文档说明，很好的实现了特征提取与匹配，该方法较基本的SIFT有很大的提高(Extraction and matching of features based on SUFT, detailed content of the documentation, very good realization of the feature extraction and matching, SIFT the method is basic is greatly improved)

说明：  PWLS算法主要用于CT重建前的投影数据处理，能够很好的用于CT迭代算法中，对图像进行去噪(PWLS algorithm is mainly used for projection data processing before CT reconstruction. It can be well used in CT iterative algorithm to denoise images.)

本代码主要是harris角点提取，ncc算法进行粗匹配，然后ransac算法剔除误匹配点(harris ncc ransac)