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用matlab写的sift算法的全过程，用于提取特征点，是图像识别的一种好算法(The algrithm of sift)

2维图像的透视变换，空间变换，可对拍摄的图像进行几何校正(Perspective transformation, the two-dimensional image space transformation, the geometric correction of images taken)

基于mind相似性度量的图像配准，配准精度很高。效果不错。(Mind based on similarity measure of image registration, the registration precision is high. The result is right.)

MKL多核学习综述文章对应的很多MKL代码的合集，里面有很多有代表性的代码，非常详细！(MKL multicore learn many review articles MKL code corresponding collection, there are a lot of representative code, very detailed!)

一种新的改进的LBP特征提取方法，采用多块比较的方法(a new LBP feature extraction method)

MATLAB实现数字图像处理和函数绘图的学习，不仅可以掌握基本MATLAB的使用，而且是数字图像处理的入门级学习。(The learning of digital image processing and functional drawing by MATLAB can not only grasp the use of basic MATLAB, but also be an entry-level learning of digital image processing.)

从原始图像产生噪声图像，使用db1执行2层小波，使用wpbmpen进行全阈值选择，采用硬阈值和软阈值处理方式,保存低频,进行图像降噪，并绘制各分解系数图像。(Generated noise image from the original image, using db1 wavelet perform two layers using wpbmpen full-threshold selection, using hard threshold and soft threshold approach, saving low frequency, image noise reduction, and draw the decomposition coefficients images.)

该代码用于实现视觉目标跟踪研究中的协方差跟踪，能够把多种时空特征融合于统一的模型中，在实现视觉目标跟踪时具有较好的鲁棒性，而且其维数等于使用特征的数量，与各个特征的维数无关，因此，其计算复杂度较小，实时性较好。(This code is used to realize covariance tracking in the research field of visual object tracking of computer vision. It enables fusion of various spatial-temporal features into an unified object feature model, hence robust to noise. In addition, its dimension is equal to the number of the features used and independent of the dimensions of the features used. Therefore, it satisfies the requirement of real-time application due to its low computation cost.)

有关目标的匹配跟踪代码，简单易懂，里面含有丰富的测试图片，和最终的测试效果图(The target matching tracking code, easy to understand, which contains a wealth of test images, and the final test renderings)

医学图像处理方面的一些基础算法，VC环境下编译的一个非常好的程序框架(Medical image processing, some of the basic algorithm, VC compiled under the framework of a very good program)