GS_Angular_spectrum

描述OFDM高峰均功率比（PAPR)的CCDF曲线，用MATLAB仿真的结果(Description OFDM peak-average power ratio (PAPR) of the CCDF curve, the results of simulation using MATLAB)

梯度矢量扩散控制实现边缘保持的彩色图像去噪(Gradient vector diffusion denoising realize control color image edge preserving )

说明：  图像处理的位图操作，256色转为灰度图，图像处理入门源程序(Bitmap image processing operations, 256-color to grayscale, image processing, entry-source)

说明：  使用sift进行的图像拼接，matlab语言实现(Image mosaic using sift)

说明：  example used in Python & VTK

说明：  This book is targeted at R programmers who want to learn the graphing capabilities of R. This book will presume that you have working knowledge of R.

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 )

基于光流法的二维单模态图像配准，能得到变形场(This will allow you to generate the deformation field needed for contour guided multi-modal image registration.)

说明：  全变分去噪程序，用于图像去噪，该方法能克服图像去噪中的震荡效应，使图像更加光滑，并能保存边缘信息。(total variation denoisy)

用matlab实现的基于广义S变换的图像去噪分型处理方法，简单易读(Using matlab realize the generalized S transform-based image denoising typing treatment methods, a simple easy-to-read)