bpsko_analysis

用模糊集方法进行图像增强，先对源图像做模糊化，然后在模糊平面上进行变换，最后再反模糊化，从而达到模糊集图像增强的目的。(Image enhancement using fuzzy set method, the first source image blurring, and then transform the fuzzy plane, and finally anti-blurring, so as to achieve the purpose of the fuzzy set of image enhancement.)

说明：  光流场经典算法-LK算法，通过两幅图像计算光流场。(Lucas – Kanade Motion Estimation using Pyramids)

说明：  Jpeg算法源代码，包含jpeg的各种算法实现的vc++的源代码(Jpeg algorithm source code, including the various algorithms jpeg of vc++ source code)

sift算法在cv领域的重要性不言而喻，该作者的文章引用率在cv界是number1.本篇博客只是本人把sift算法知识点整理了下，以免忘记。本文比较早的一篇博文opencv源码解析之(3)：特征点检查前言1 中有使用opencv自带的sift做了个简单的实验，而这次主要是利用Rob Hess的sift源码来做实验，其实现在的opencv版本中带的sift算法也是Rob Hess的，只是稍微包装了下。 下面来做下试验,试验sift代码采用Rob Hess的代码，opencv目前版本中的sift源码也是采用Rob Hess的。代码可以在他的主页上下载：http://blogs.oregonstate.edu/hess/code/sift/ 这里我下载的是windows版本的，并采用Qt做了个简单的界面。(sift algorithm is self-evident the importance of the cv field, the author of the article referenced in the cv sector is number1 this blog I just sift algorithm knowledge compiled under, so as not to forget. This article compares the earlier blog post opencv source code analysis (3): check the preface of the feature points 1 the opencv bring their own sift to do a simple experiment, but this time Rob Hess' s sift source to experiment. In fact, with the opencv version sift algorithm is Rob Hess, only slightly packing the next. Below to do the next test, test sift code using the code of Rob Hess, sift source opencv version of Rob Hess. The code can be downloaded on his home page: http://blogs.oregonstate.edu/hess/code/sift/ here I downloaded the windows version, and using Qt to do a simple interface.)

局部拉普拉斯滤波代码，效果很好，可以直接运行(Edge-aware Image Processing with a Laplacian Pyramid)

说明：  医学图像图像配准方法，采用了经典的基于灰度的方法。(This is a general purpose registration method for medical images. )

细节增强的直方图均衡法，在增强图像对比度的同时还能保留细节细心，避免了细节吞噬现象(Detail enhancement, histogram equalization, but also retained the same time enhance the image contrast details carefully, to avoid the details of phagocytosis)

k均值聚类，聚为2类，结果显示散点图，红色十字表示聚类中心(K-means clustering, the class number is 2, and the results showed that the clustering center)

说明：  XYZ视频图像压缩编码的应用原理与实际生活应用 (XYZ video image compression encoding)

根据16点DFT算法得出的运算流程图，得到的16点DFT蝶形运算函数(16 point s DFT algorithm)