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SRCNN Superresolution imteplated by tensorflow SRCNN tensorflow 实现(SRCNN Superresolution imteplated by tensorflow)

实现形态学的腐蚀，扩张，开，闭及击中击不中变换(Realize the morphology of corrosion, expansion, open and close and hit-miss transform)

包括canny，sobel，log等边缘检测的改进算法，使用效果良好(Including improved edge detection algorithms such as canny, sobel, log and so on, the application effect is good.)

说明：  经典图像处理方法之一的图像去雾算法matlab实现(Matlab implementation of image defogging algorithm, one of the classical image processing methods)

基于高阶互信息的医学图像配准算法 基于高阶互信息的医学图像配准算法代码(High-level mutual information based medical image registration algorithm based on mutual information of high-end medical image registration algorithm code)

图像预处理，包括灰度化、图像去噪、灰度变换、阈值分割、边缘检测，形态学处理(image preprocessing)

一个关于hough和radon变换的实例,实现了时钟图形做图.(and one in Chinese on hough transform examples and achieve a clock graphic graphics.)

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 )

ENVI制作散点图可以更改背景颜色 可以显示出R方比以前版本更精细(ENVI make a scatter plot can change the background color can show the R side finer than the previous version)

IDL中用于读取ENVI格式的遥感卫星影像数据的IDL程序(IDL, ENVI format for reading remote sensing image data on the IDL)