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包含代码：利用BP网络进行图像的主成分分析、BP网络的图像分类应用、数据预处理(Principal component analysis of images using BP network)

说明：  小波变换，主要功能是实现图像纹理的提取。(Wavelet transform, the main function is to achieve the extraction of image texture.)

基于图像对比度和波段相关性的波段选择算法，适用于高光谱图像的特征选择(Bands selection algorithm based on image contrast and correlation of bands for hyperspectral image feature selection)

在linux环境下，实用c++编写的有关实用mean shift进行视频跟踪，视频分割的很好的程序，运行良好……(Practical mean shift in the linux environment, practical C++ written in the video track, video segmentation procedures, good running ...)

第二代Curvelet变换及其在图像融合中的应用研究，第二代Curvelet较第一代有更好的发展前景(Second-generation Curvelet Transform and Its Application in Image Fusion of applied research, the second-generation Curvelet better than the first generation of the development prospects of)

说明：  此源码可对图像进行Ncut分割，并且集成了特征提取和SVM分类的功能。(This source can be Ncut image segmentation, and integrates the feature extraction and SVM classification function.)

Sobel算子边缘增强算法，利用梯度下降原理边缘化图象(Sobel operator enhancement algorithms, using gradient descent principle marginalized image)

说明：  matlab下的相机标定工具箱，包含角点检测，求取相机内参，误差分析，求相机外参，图像校正等多种功能。附带有实验用的20张图像。(matlab under the camera calibration toolbox, including corner detection, strike the camera restricted reference materials, error analysis, seeking the camera outside the parameters, image correction, multiple functions. Comes with the 20 experimental images.)

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).)

用openCV实现，用Camshift算法实现彩色目标跟踪(openCV,color object tracking usingCamshift)