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MaYiTaC-PCP
- 低秩矩阵与稀疏表示应用，大致的介绍了低秩矩阵与稀疏表示在图像处理以及其他领域的作用-Low-rank matrix and sparse representation of the application, the approximate low-rank matrix and sparse representation in image processing and other areas
GoDec
- 关于噪声存在时，矩阵的低秩与稀疏分解。做图像处理的有用
Bayesian-Image-code-new
- 使用改进型贝叶斯对矩阵进行低秩处理，进而应用到图像处理方便-Improved Bayesian use low rank matrix processing, and then applied to the image processing convenience
DIP
- 包含基于三种不同方法的应用于图像处理的矩阵低秩分解的matlab算法，可以将目标图像分解为一个低秩图像和一个稀疏图像之和；并包含一种基于区域生长方法的图像区域识别程序，可以用来提取图像中的目标。-Containing used in image processing based on three different methods of low-rank matrix decomposition algorithm matlab, the target image can be decompos
lrr(motion_face)
- 本程序是用来处理图像，把代表图像的矩阵分解成为一个低秩矩阵和一个稀疏矩阵~-This procedure is used to deal with the image, the representative image of the matrix decomposed into a low-rank matrix and a sparse matrix ~
as_rpca
- 本程序主要是处理图像的，主要是用于求解被高幅度尖锐噪声而不是高斯分布噪声污染的信号分离问题~把问题矩阵分解成一个低秩表示的矩阵和一个稀疏矩阵，优化目标函数，用ALM方法是求解的~-This procedure is mainly to deal with the image, mainly for solving high-amplitude sharp noise rather than Gaussian noise distribution of the signal separation
基于结构稀疏的SAR图像低秩重建
- 压缩感知图像处理用于SAR 经典的压缩感知教科书的源代码(compressed sensing SAT)
Approximate low-rank projection1
- 在文中，提出来一个基于低秩的特征提取方法(Feature extraction plays a significant role in pattern recognition. Recently, many representation-based feature extraction methods have been proposed and achieved successes in many applications. As an excellent unsupervised featu