Hyperspectral-Data-Classification

含有Matlab的各种程序和代码，包括图像分割、模式识别、文字识别等。并且含有初学者入门的代码。(Matlab contains the various procedures and code, including image segmentation, pattern recognition, text recognition. And contain the code entry for beginners.)

本程序将SIFT与边缘结合起来用来做图像配准 先用SIFT检测关键点 用CANNY算子进行边缘检测 进而优化选取最佳匹配点 进行向量匹配 图像配准。 (The program will combine the SIFT and the edge of image registration is used to make the first detection of the key points with SIFT operator with CANNY edge detection and then select the best match point optimized vector matching image registration.)

对于一个二值图像骨架化之后进行边缘平滑，滤波，效果非常不错，适合于任何二值图片(After a binary image is skeletonized, it is smoothed and filtered. The effect is very good. It is suitable for any binary image.)

遥感信息工程学院遥感原理与应用课程实习植被指数(Vegetation Index of Remote Sensing Principle and Application Course Practice)

一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。(A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds)

图象的冲击滤波程序,用于图象增强,用MATLAB语言编写(image filtering impact procedures for image enhancement, using MATLAB language)

本代码主要是harris角点提取，ncc算法进行粗匹配，然后ransac算法剔除误匹配点(harris ncc ransac)

图像处理入门教程，比较适合初学者，对于图像知识有所掌控，内容比较详细。(Image Processing Getting Started tutorial, suitable for beginners, more detailed image of knowledge has been the control.)

图像配准程序，包括角点提取，配对，提纯等操作(image registeration ,including connor detection,match and so on)

给定一副图像，采用一定的策略对其进行搜索以确定其中是否含有人脸，如果是则返回一脸的位置、大小和姿态(人脸检测)