TDPCA

基于matlab的指纹识别源码 包括预处理、特征点提取和特征点匹配(Fingerprint recognition source code based on MATLAB includes preprocessing, feature extraction and feature matching)

基于Fisher线性判别基础学习器的集成分类器专门用于数字媒体的隐写分析，目前使用高维特征空间。目前，由于其良好的检测精度和较小的计算成本，它可能是设计监督分类器用于数字图像隐写分析的最常用方法。(The ensemble classifier, based on Fisher Linear Discriminant base learners, was introduced specifically for steganalysis of digital media, which currently uses high-dimensional feature spaces. Presently it is probably the most used method to design supervised classifier for steganalysis of digital images because of its good detection accuracy and small computational cost. It has been assumed by the community that the classifier implements a non-linear boundary through pooling binary decision of individual classifiers within the ensemble.)

说明：  usps数据库为标准手写数据库，此为mat数据文件，含训练集和测试(USPS database is a standard handwritten database, which is a mat data file, including training set and test)

基于rtklib计算加入北斗的单点定位及差分定位(single PP and DGNSS using BEIDOU based on RTKLIB)

主要功能是实现相机标定，以及实现反投误差，实现特征点的提前。(The main function is to achieve camera calibration and error to achieve the anti-investment, to achieve the feature points in advance.)

程序实现图像分块，凸包，分割等功能，学图像处理的朋友建议下载。(Image sub-block implementation procedures, convex hull, partition and other functions, the study image processing Friend recommended download.)

用拉普拉斯金字塔的方法，对两幅聚焦位置不同的图象进行融合处理，获得更清晰的图象。(Laplace pyramid, focusing on two different positions of the image fusion, more clearer picture.)

说明：  提取图像中的模式噪声，是先使用滤波器后再进行提取的(To extract the pattern noise in an image, a filter is used first and then the noise is extracted)

在自适应中值滤波的基础上，采用均值与方差得到一个阈值，来判断极值点是不是噪声点！(On the basis of adaptive median filtering, a threshold is obtained by means of mean and variance to determine whether the extreme point is a noise point!)

说明：  高光谱图像数据集，Pavia University scene该数据是高光谱图像处理中常用的数据之一，对高光谱图像算法性能的验证具有通用性(Hyperspectral image data set, Pavia University scene This data is one of the commonly used data in hyperspectral image processing, and it has universality to verify the performance of hyperspectral image algorithm)