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erzhituxiangCS
- 读取二值图像，转化为稀疏信号，变换到压缩域，然后用压缩感知进行重构。-Read binary image, into sparse signal, transform to the compressed domain, and then use compressed perception reconstruction
cs
- 利用压缩感知对图像进行处理 先用小波变换生成矩阵，再利用正交匹配追踪算法，在对图像进行稀疏处理后进行正交匹配追踪 -Orthogonal matching pursuit algorithm for image processing First generated using wavelet transform matrix orthogonal matching pursuit, sparse processing im
Sparse-point-matching
- 基于opencv的稀疏点匹配与重建（无图像校正）-Sparse point matching and reconstruction (no image correction)
SRC
- Sparse Representation for accurate classification of corrupted and occluded facial expressions使用稀疏表示方法对有遮挡和腐蚀的人脸表情图像进行分类-Sparse Representation for accurate classification of corrupted and occluded facial expressions
KSVD-for-SAR_LOG
- 用基于稀疏表示和KSVD字典学习去噪方法在对数域对SAR图像抑斑，本方法相对于一些经典的SAR图像抑斑方法，抑斑效果大大提高。-Based on the sparse representation and KSVD dictionary learning denoising method in the logarithmic domain，we despeckle SAR image, compared with some of the
Mixedthreshold_Image-Recovery
- 代码给出了基于混合门限带迭代步长的稀疏图像重构。特别地，压缩采样矩阵为抽样傅里叶变换矩阵，利用2D-FFT,大大降低了计算复杂度。-The mixedthreshold sparse image reconstruction with step is given in the package. In particular， the 2D-FFT is used to disign the sample matrix, which can
demo
- KSVD图像去噪,组稀疏编码，新的去噪思路-KSVD image denoise，group spare coding
sichashu
- 选择使用matlab对图像进行四叉树分解，并且显示稀疏矩阵的结果。-Choose to use the matlab quadtree decomposition of the image, and sparse matrix results.
KSVD-P-Sparse-Representation
- K-SVD SPARSE REPRESENTATION 基于学习的稀疏表示图像分析方法，以去噪为例。-K-SVD SPARSE REPRESENTATION
u3vw1x.ZIP
- 基于图像导数框架和非负稀疏编码的颜色恒常计算方法Based on image derivative fr a me and the non negative sparse coding of color constancy computation method-Based on image derivative fr a me and the non negative sparse coding of color constancy c
MaYiICIG-Theory
- 低秩矩阵与稀疏表示原理，详细的说明了用低秩矩阵与稀疏表示去分离一个有噪声的图像-The low-rank matrix with sparse principle, a detailed descr iption of the low-rank matrix with sparse to isolate a noisy image
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
sparse-points-and-matching
- 稀疏点匹配与重建（无图像校正），结合OpenCV开放-sparse points and matching
CSR_denoise
- 一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果-a image denoising method with structral clustering and sparse representation, has good effect .
TILT_v1_04
- 一种求解低秩矩阵和稀疏矩阵的方法，在图像中的应用广泛。-a inprove method to find low-rank and sparse matrix。
k_svd
- 利用稀疏采样对图像进行去除噪声与图像重建-Sparse sampling of the image noise removal and image reconstruction
ACHA05_Inpaint
- 基于信号稀疏分解的形态成分分析来进行图像的分解和修复原作者的英文原文献-Morphological component analysis based on the signal sparse decomposition of the image decomposition and restoration of the original author of the original English literature
sichashufenjie
- 对示例图像进行四叉树分解，并以图像的形式显示所得的稀疏矩阵，同时取得所有子块和符合各种维度条件的子块数目。-Quadtree decomposition of the sample images, and the form of images obtained sparse matrix, at the same time to obtain the number of sub-blocks of all sub-blocks and
sparse-points-and-matching
- 稀疏点匹配与重建的好例子,没有图像校正的过程-sparse points and matching
SensingMatrixDesign
- 利用块稀疏的方法求解感知矩阵，在压缩感知、图像恢复方面都可以应用-Method for solving block sparse perception matrix in compressed sensing, image restoration can be applied