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基于matlab的稀疏表示中L1范数计算源码
- 基于matlab的稀疏表示中L1范数计算源码,the codes for L1 in sparsty representation with matlab
compress edsensing OMP
- 压缩感知 正交匹配追踪一些人关心压缩感知与雷达成像，他们把稀疏表示放在最重要的地方，以为在雷达成像中成功实现压缩感知关键是稀疏表示； 事实上并不是如此。我们知道：压缩感知需要建立AX=B,且该方法具有较低的抑制信噪比能力；另外雷达成像的基础是雷达 信号与目标的相互作用，也就是电磁波与介质的相互作用，该相互作用是一个非常复杂的非线性问题，因此研究这个问题与 压缩感知的关系才是解决雷达成像问题的关键点所在。从另外一个角度来看，雷达成像中惯用的方法是匹配滤波，
Matlab-Code-for-Image-Representation
- 附件程序为图像稀疏表示的源代码，程序用matlab编写，能正常运行。-Sparse representation of the image attachment program source code, programs written with matlab able to function properly.
KSVD_Matlab_ToolBox
- KSVD原始算法：信号稀疏表示中的过完备字典的学习算法-KSVD original algorithm: Signal Sparse Representation of the learning algorithm over-complete dictionary
ompbox
- 稀疏表示正交匹配追踪算法matlab源代码-sparse representation
sparse_representation
- 最热门的稀疏表示的算法，马毅等人在PAMI上发表的文章代码-Sparse representation of the most popular algorithms, Yi Ma, and others published an article in the PAMI code
K-SVD工具箱
- 用于信号稀疏表示的K-SVD字典学习算法工具箱，有详细的Demo，方便理解。
gabor_function.m
- 自己写的Gabor方程函数，可以用来产生过完备的稀疏表示字典。-Gabor write their own equation function, can be used to generate the sparse representation over-complete dictionary.
OMP
- 正交匹配跟踪算法: 是贪婪算法中稀疏求解的方法-Orthogonal matching pursuit algorithm: Solving Sparse
KSVD_Matlab_ToolBox
- 应用于稀疏表示的KVSD算法，MABLAB-KVSD algorithm applied to sparse representation, MABLAB
Matlab-for-Image-Representation
- 图像稀疏表示的MATLAB编程代码，有图-MATLAB sparse representation of the image programming code, a map
KSVD_Matlab_ToolBox
- 图像稀疏编码的一种方法，可用于基于稀疏表示的图像压缩、去噪等-Sparse image coding method can be used for sparse representation-based image compression, denoising, et
lunwen
- 关于图像稀疏表示的鲁棒掌纹处理，在国内很少有基于稀疏的掌纹处理文章-Robust sparse representation on the palm print image processing, very few in the country' s palm with posts based on sparse
Sparse-and-Redundant-Representations
- Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing，稀疏表示的最新巨作-Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing, sparse representation of the latest blockbuster
l1_ls
- 稀疏表示分类算法，用于样本分类的数学算法-Sparse that classification algorithms, mathematical algorithms for sample classification
eccv10_tutorial_part2
- 稀疏编码图像分类, 稀疏表示创始人写的PPT,内容精彩,分析清晰,易于理解(sparse coding image classification, PPT written by the original author of sparse representation, the PPT content is easy to realize with clear illustration and analysis.)
SPAMS
- 先输入数据生成相应的字典，再输入检测信号后得到用字典稀疏表示的结果(First input data, generate the corresponding dictionary, and then input the detection signal to obtain sparse dictionary results)
稀疏分解
- 信号稀疏表示的目的就是在给定的超完备字典中用尽可能少的原子来表示信号，可以获得信号更为简洁的表示方式，从而使我们更容易地获取信号中所蕴含的信息，更方便进一步对信号进行加工处理，如压缩、编码等(Signal sparse representation is to overcomplete dictionary given in as little as possible to represent atomic signal, signal can be more succinct represen
RieszWavelet(TIP2)
- 使用小波框架并结合稀疏表示，用于SAR图像的目标识别应用(Application of wavelet frame and sparse representation for target recognition in SAR images)
FDDL
- 基于Fisher字典学习的稀疏表示分类算法。(Sparse representation classification algorithm based on Fisher dictionary learning.)