sift-introduction

说明：  多目标跟踪，动态背景下实现多目标跟踪算法，算法优良，实时性和鲁棒性都比较好(Tracking, dynamic context to achieve multi-target tracking algorithm, algorithm quality, real-time and better robustness than)

基于MATLAB实现图像融合，左右焦距融合(Image fusion based on MATLAB,Left and right focal length fusion)

图像处理中的数字识别代码，包括数字训练集合和训练分类算法，可以实际应用。(digital recognition)

展示了汽车行业的应用案例。任务是利用标定的可变形匹配来定位不同方向和位置的车门(3D variable model matching)

说明：  修改文件存储路径及相关参数,此代码可读取nc格式的文件(After modifying file storage path and related parameters,this code can read the data with the format of 'nc')

Image processing functions: Gamma correction Contrast stretching histogram equalization

全套的DCT域数字水印源代码matlab(A full set of digital watermarking of DCT-domain source code matlab)

这是针对波前编码成像系统模拟，以及图像复原模拟代码(this is the wavefront coding image processing code of WFC optic system. it is very useful in WFC syetem for research .)

在统计学中，皮尔逊积矩相关系数（英语：Pearson product-moment correlation coefficient，又称作 PPMCC或PCCs[1], 文章中常用r或Pearson s r表示）用于度量两个变量X和Y之间的相关（线性相关），其值介于-1与1之间。在自然科学领域中，该系数广泛用于度量两个变量之间的相关程度。它是由卡尔·皮尔逊从弗朗西斯·高尔顿在19世纪80年代提出的一个相似却又稍有不同的想法演变而来的。这个相关系数也称作“皮尔森相关系数r”。(In statistics, Pearson product-moment correlation coefficient (English: Pearson product-moment correlation coefficient, also known PPMCC or PCCs [1], the article used or Pearson s r r representation) is a measure of the two variables X and Y between correlation (linear correlation), a value between-1 and 1. In the natural sciences, the coefficient is widely used to measure the degree of correlation between the two variables. It is made a similar Karl Pearson Francis Galton in the 1880s but made a slightly different idea evolved. The correlation coefficient is also called Pearson s correlation coefficient r .)

一款VC++图像开场加载效果，向大家演示了几种图像装载的特效实现的方法，比如扫描显示、滑动显示、渐入显示和马赛克显示等，大家在使用一些幻灯片软件的时候，经学会看到类似的效果，如果你有一定的VC++基础，你可以借鉴一下本效果的具体方法，再次扩展，可以制作出一款带特效的图像查看器(The opening loading effect of a VC++ image to demonstrate the effects achieved in several image loading, such as scanning, slide show, getting into the display and mosaic display, we learn to look at some slides software to similar effect, if you have certain VC++ basis, you can learn about the effects of specific methods, extended again, can create the image of a band effects Viewer)