surface-quality-detection

是国外大牛编写的，对图像进行二维反卷积恢复代码,该代码主要针对图像的失焦模糊。(Prepared by the large foreign cattle 2D deconvolution, image recovery code.)

本程序是实现图像处理的关于调色板的设置功能。(This program is a set of image processing functions on the palette)

暗原色先验的视频去雾算法 matlab实现(the code of defog using dark-chanel prior algorithm)

区域生长 冈萨雷斯 matlab 集合了区域生长函数和使用过程文件(The region growing Gonzalez matlab collection of regional growth function and process of using file)

边缘检测法和阈值分割法，是图像分割技术应用中两项重要的方法。本文介绍了图像边缘检测和阈值分割的一般原理、典型算法以及研究现状。本文针对边缘检测算子和几种阈值分割技术进行了详细讨论。针对火柴根数统计和钢筋根数统计两个实验，在详细分析检测原理的基础上，编写了相应的实验并给出了实验结果。(Edge detection and thresholding method, image segmentation is an important technology in two ways. This article describes the general principles of image edge detection and thresholding, the typical algorithms and research status. In this paper, several edge detection operator and thresholding techniques are discussed in detail. Statistics for the number of matches and reinforced the number two experimental statistics, based on a detailed analysis of the detection principle, write the corresponding experimental and experimental results are given.)

基于opencv的radon直线检测、直方图均衡、sobel边缘检测等算法。(Opencv of the radon-based line detection, histogram equalization, sobel edge detection algorithm.)

SSDA序贯相似性检测方法对图像进行模板匹配。从源图像中取小图，再到源图像中找到小图所处的位置。(SSDA sequential similarity detection method of the image template matching. Source image taken from the small map, to find a small map the source image position.)

New Tracking Algorithm for Wireless network

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 )

基于各向异性扩散的医学图像的边缘检测与分割处理(Based on the anisotropic diffusion of medical image segmentation and edge detection)