搜索资源列表
MP
- 稀疏表示中的一种重构算法,贪婪算法,通过逼近来寻找局部最优解-Sparse representation of a reconstruction algorithm, greedy algorithm, by approaching to find a local optimal solution
ShearLab-PPFT-1.0
- 图形处理中需要用到的剪切小波变换。可以稀疏表示信号。-Graphics processing needed shear wavelet transform. Sparse representation of the signal.
MP
- 稀疏表示的MP程序,已调试,可以直接使用哈!主要用于图像压缩,图像去噪等方面。-code for mp
APBT
- 代码使用全相位双正交变换(APBT)稀疏表示图像,主函数为test.-The code uses the all phase biorthogonal transform (APBT) sparse representation of the image, the main function for the test.
txys
- 压缩感知的获取与重建,信号的稀疏表示,测量矩阵,重建算法-Compressed sensing acquisition and reconstruction
PAMI-Face
- 稀疏表示在鲁棒性人脸识别中的应用,很经典的论文-Sparse representation in the robustness of face recognition, very classic papers
(PAMI-new)
- 稀疏表示在人脸识别中的应用(最新版),很经典论文-Sparse representation in face recognition (latest edition), classic papers
PAMI_Feature
- 稀疏表示中,关于如何提取特征的介绍。很值得看-Sparse representation, introduction on how to extract features. Is worth a look
Image-Super-Resolution-Via-SR
- YANG JC 2010年基于稀疏表示的图像超分辨PPT,全英文-Yang JC 2010 super-resolution image based on sparse representation PPT, English
05466111
- 杨建超 基于稀疏表示的图像超分辨 2010年文章-YANG JC Image Super-Resolution Via Sparse Representation
goodbook
- 里面介绍了很多小波分析、稀疏表示、盲源分离方面的书籍-Which introduced a lot of wavelet analysis, sparse representation and blind source separation of books
Sparsity-Collaborative-Track
- 基于稀疏表示的目标跟踪,对于稀疏表示应用于图像处理的同志可是一个借鉴。-Robust Object Tracking via Sparsity-based Collaborative Model
SpRegKL1
- 基于交替方向乘子法的核稀疏表示算法,其中约束为L1规则-Alternating direction multiplier method based on nuclear sparse representation algorithm, which is L1 constraint rules
KOMP
- 核稀疏表示的正交匹配追踪算法,这里核稀疏表示的正则化项为L0范数-Nuclear sparse representation orthogonal matching pursuit algorithm, where nuclear sparse representation regularization term is L0 norm
SolvePFP
- 图像等运用稀疏表示的方法进行计算识别和分类-Images using sparse representation method to calculate identification and classification
KSVD_Matlab_ToolBox
- 这是线性训练K-SVD词典的一种新算法 表示的信号。给定一组信号,K-SVD试图 提取物,可以稀疏表示这些信号最好的词典。 深入讨论了K-SVD算法中可以找到的: “K-SVD:设计的超完备字典的一个算法 稀疏表示”,由M.阿哈,M. Elad和点写,适应性, 在IEEE Transactions出现。在信号处理,卷54,11号, 第4311-4322,十一月2006
paper1
- 论文一篇:基于稀疏表示的信号DOA估计.pdf-Based on sparse representation signal DOA estimation. Pdf
Autofocus-ISAR-Sparse-represetation
- 基于稀疏表示的逆合成孔径雷达自聚焦成像,讲述了自聚焦方法-Based on sparse representation inverse synthetic aperture radar imaging self-focusing
SparseRepresentationaItsApplication
- 稀疏表达及其应用的简单介绍,其中涵盖了稀疏表示、特征提取、压缩感知、图像增强、盲源分离、模式分类、目标跟踪和图像超分辨等。PPT和PDF是对应的,并添加了可视化的结果。-Sparse Representation and Its Application: Compressive Sensing, Visual Feature, Image Enhancement, Blind Source Separation, Pattern Cla
xishuquzao
- 信号的稀疏表示,它意欲用尽可能少的非0系数表示信号的主要信息,从而简化信号处理问题的求解过程-Signal sparse representation, it intends to as little as possible of non-zero coefficient signal is the main information, so as to simplify the solving process of signal pro