masksample

RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。目前最有效的算法是ALM（Augmented Lagrange Multiplier）。ALM分为Exact ALM和Inexact ALM。 该代码是Inexact ALM，收敛速度比Exact ALM快！(RPCA (Robust Principal Component Analysis) is used for matrix filling, image denoising. It is currently the most effective optimization method. Currently the most effective method is ALM (Augmented Lagrange Multiplier). There re 2 kinds of ALM: Exact ALM and Inexact ALM. The code is Inexact ALM, faster convergence speed than the Exact ALM!)

高光谱图像进行MNF变换，采用MAF评价图像的噪声；处理过程与ENVI软件中的完全一样。(MNF transformation of hyperspectral images, using noise MAF to evaluate the image.the process is exactly the same with ENVI software .)

目标运动的真实轨迹和估计轨迹，以及所进行的误差分析(Target motion trajectory and estimate the true trajectory, and error analysis conducted)

通过sift特征提取实现两幅图片无缝拼接(Seamless splicing of two images by SIFT feature extraction)

robustly fits a homography to a set of putatively matched image points(robustly fits a homography to a set of putat ively matched image points)

使用二维双密度小波2-D Double-Density DWT Thresholding Method，决定图像滤波门限值，实现图像去噪处理。(use of two-dimensional density Wavelet 2-D Double-Density DWT Thresho lding Method, the decision threshold image filtering, image denoising.)

说明：  对数据的独立性进行分析，对数据的预处理（中心化和白化处理）(The independence of data analysis, data pre-processing (center-based and the whitening process))

时频峰值滤波（TFPF）算法是一种非常有效的去噪方法(TFPF is a effective method.)

图像检测，目标检测简单来说就是找出图像中的目标并给定目标的位置，一般用矩形框定位出目标(In image detection, target detection is simply to find out the target in the image and give the location of the target. In general, the rectangular box is used to locate the target)

该程序是发表在IEEE上的经典直线提取论文“Extracting Straight Lines”的源代码实现，对计算机视觉、模式识别和信息提取等领域的科学研究人员具有极其重要的参看意义。建议下载学习和适用。(The program is published in the IEEE paper on the classic straight-line extraction " Extracting Straight Lines" the source code implementation of computer vision, pattern recognition and information extraction and other areas of scientific researchers see an extremely important significance. Recommended to download to learn and to apply.)