BP

视觉测量中编码点与非编码点的匹配的方法实现(Vision measuring, coding point and the coding point matching )

对偏振图像进行融合处理。其中包括比较经典的小波变换，ihs垂直变换以及拉普拉斯金字塔变换。。。(The polarization image fusion processing. Including the more classic wavelet transform, ihs vertical transformation and Laplacian pyramid transformation. . .)

KLT point match:Detection and Tracking of Point Features.

这是经典的SAR成像算法，包含了RDA CSA RMA三种常见的对于点目标的成像算法(This is classic SAR imaging algorithm, including the RDA CSA RMA three common for point target imaging algorithm )

说明：  从单张图片中去除相机抖动造成的模糊的matlab程序，算法见Removing Camera Shake from a Single Image(err)

晨宇思远博客的代码------文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明( morning yu siyuan blog code----------- file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are detailed description file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are elaborate)

从原始图像产生噪声图像，使用db1执行2层小波，使用wpbmpen进行全阈值选择，采用硬阈值和软阈值处理方式,保存低频,进行图像降噪，并绘制各分解系数图像。(Generated noise image from the original image, using db1 wavelet perform two layers using wpbmpen full-threshold selection, using hard threshold and soft threshold approach, saving low frequency, image noise reduction, and draw the decomposition coefficients images.)

说明：  小波去噪 matlab小波去噪详解超全超全有程序,小波去噪，硬阈值软阈值(Wavelet denoising Matlab wavelet de-noising details super full super full program, wavelet de-noising, hard threshold soft threshold)

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)

VC计算机图形学原理及算法教程 VC计算机图形学入门教程(VC theory and algorithms of computer graphics computer graphics tutorial Tutorial VC)