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高光谱图像的地物分类技术，对光谱分析并对比检测出地景的算法(Fifth hyperspectral image classification techniques, algorithms for spectral analysis and contrast detect landscapes)

sift特征点检测及图像拼接，matlab7.0实现的，我从别人那里整过来的，测试的话，用在matlab里面直接调用match( b1.jpg , b2.jpg )即可，我测试成功，里面也有说明文档，为了科研，共享，希望大家有好的代码都0分共享，与己方便，与人方便，中国科研才会发展更迅速(sift feature point detection and image stitching of, matlab7.0 realized, I come from others where the whole test, used in matlab inside direct calls to match (' b1.jpg' , ' b2.jpg' ) can I test success, which also has documentation, in order to research, share, and hope everyone has a good code sharing, and has convenient, and accommodating, the more rapid development of China' s scientific research will)

bresenham画直线，WIN32，计算机图形学基础类源代码(bresenham画直线)

边缘检测 Edge Detection Edge Detection(Edge Detection)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

说明：  VC的一些工程案例，包括车牌识别，人脸识别，图像处理基本操作等(car license recognization system)

程序设计步骤： 1、去均值 2、计算协方差矩阵及其特征值和特征向量 3、计算协方差矩阵的特征值大于阈值的个数 4、降序排列特征值 5、去掉较小的特征值 6、去掉较大的特征值(一般没有这一步） 7、合并选择的特征值 8、选择相应的特征值和特征向量 9、计算白化矩阵 10、提取主分量(Programming steps: 1 to mean 2, calculation of covariance matrix and its eigenvalues and eigenvectors 3, the calculation of covariance matrix eigenvalues greater than the threshold number of 4, in descending order of eigenvalue 5, remove the smaller eigenvalue 6, remove the larger eigenvalue (usually not this step) 7, the combined choice of eigenvalues 8, select the appropriate eigenvalues and eigenvectors 9, computing whitening matrix 10, principal component extraction)

说明：  多边形裁剪是逐次多边裁剪法，它的基本思想是以窗口的四条边界线单一逐次对多边形裁剪(polygon clipping is Successive multilateral cutting, its basic idea is a window four successive boundaries of a single polygon clipping)

K均值聚类算法对图像进行分割，实验用程序，亲测可用。(K-means clustering algorithm for image segmentation, experimental procedures, pro-test is available.)

利用visualC++和图像处理的知识，编写程序对果蔬进行自动识别(Using visualC++ and image processing knowledge, write a program for automatic identification of fruits and vegetables)