2wei-max-entropy

通过matlab实现jpeg图像压缩编码。(To realise jpeg coding.)

高光谱图像目标检测ACE算法，适用于已知目标信息情况(HYPERACE Performs the adaptive cosin/coherent estimator algorithm Performs the adaptive cosin/coherent estimator algorithm for target detection.)

易语言仿彗星真彩PNG按钮源码，易语言写的图形图象编程，很好的参考。(Easy language imitation comet true color PNG button, easy graphics programming language to write, a good reference.)

一个光流算法的matlab源程序，在图像处理、前景检测与跟踪等方面有很多应用，推荐(An optical flow algorithm matlab source code in image processing, the prospects for detection and tracking, etc. There are many applications, the recommendation)

一种快速的算术编码程序. 也是JPEG和JPEG2000的部分核心算法.(A fast arithmetic coding procedures. JPEG and JPEG2000 is also part of the core algorithm.)

数字图像处理边缘检测算法VC源码，里面包括多种检测算子(Digital image processing edge detection algorithm VC source code,Which includes a variety of detection operator )

说明：  按照最邻近原则把待分类样本点分到各个簇。然后按平均法重新计算各个簇的质心，从而确定新的簇心。一直迭代，直到簇心的移动距离小于某个给定的值。(According to the nearest neighbor principle, the sample points to be classified are divided into clusters. Then the centroid of each cluster is recalculated according to the average method to determine the new cluster center. Iterate until the moving distance of the cluster center is less than a given value)

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 .)

图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。 其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？ 用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。 在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。(Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set. In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem? After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified. Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram )

傅立叶变换，等距离采样，等角度采样，轮廓提取，形态处理(Fourier transform, equidistant sampling, in terms of sampling, contour extraction, morphological processing)