搜索资源列表
spams-matlab-v2.2.tar
- 基于字典学习的稀疏编码，最新的版本，可以用于 window Linux和MacOs-Sparse Coding on Dictionary Learning，the new version. it can be applied to the windows, Linux and Mac
L1
- 目前比较流行的稀疏分解重构程序，可以用在人脸识别、字典构造等方面。-Currently popular sparse decomposition and reconstruction process, can be used in face recognition, dictionary structure and so on.
Face-Recognition-Gabor-Occlusion
- 发表于ECCV上的一篇用于人脸识别的算法，Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary -At ECCV on an algorithm for face recognition, Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dic
imagecodingandcompression
- 章 图像编码与压缩 图像编码基础 无损压缩编码 行程编码 哈夫曼（ Huffman ）编码 算术编码 词典编码 有损压缩编码 预测编码 正交变换编码 MATLAB 实现余弦变换压缩 17.3.4 MATLAB 实现小波变换压缩 -S image coding and compression image coding based lossless compression stroke Huffman coding (Huffman) co
MATLABhanshu
- matlab的函数目录，，作为初学者的函数字典，，很有参考价值-matlab function directory, as a function of beginners dictionary, a good reference
ssa
- 多种信号过完备字典学习算法的工具包，包含文献Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms中所有的算法。-Multiple signals over-complete dictionary learning algorithm toolkit, including literature Surveying and comparing simultaneous sparse
Metaface_ICIP
- 利用稀疏表示一集字典学习的方法进行人脸自动识别的Matlab算法，是经典SRC方法的提高-That a sparse set of dictionary use of learning methods in Matlab automatic face recognition algorithms, is the classic method of improving SRC
ScSR
- Jianchao Yang 的基于稀疏表示的单幅图像重建的原始代码，先将高低训练图像分块，再将块训练成高低字典，将测试图像映射到低字典上，得到系数，再乘以高子典就得到最后的图像。对学习超分辨率同学的参考作用很大。-This is the original matlab code for super resolution by Jianchao Yang 。The method is sparse represent based on the overcomplete dictionary。
Elad-ksvd-matlab-toolbox
- 稀疏表示，字典学习，KSVD算法，matlab版-Sparse representation dictionary learning, KSVD algorithm, matlab
ImprovedDL
- 这是一篇SCI文章《改善字典学习：多字典更新和系数重用》里的Matlab代码，包含了OMP、Batch-OMP、CoROMP等匹配跟踪算法代码以及改进的K-SVD字典学习算法代码，是图像稀疏表示研究方向重要的源代码，有助于大家学习和改进。-This file folder reproduces the Figures for paper:"Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reus
KSVD_Matlab
- 基于dictionary learning的MR图像重建的代码，希望对从事MR图像重建的朋友有用，使用matlab开的的代码-dictionary learning for MR image construction
Sparse-Representation-
- 文献“Sparse Representation based Fisher Discrimination Dictionary”及其对应的matlab代码，稀疏学习是目前非常流行的方法，希望对大家有所帮助-a paper named Sparse Representation based Fisher Discrimination Dictionary and its matlab code
forget_factor
- 字典学习dictionary learning算法中遗忘因子的设置，matlab版-Dictionary learning dictionary learning algorithm forgetting factor setting, matlab version
KSVD
- This program uses the operating environment written in MATLAB, nonlinear compression on the perception of image reconstruction to achieve, the focus is KSVD dictionary compilation.
BPFA_Denoise_04152010
- 非参贝叶斯字典学习用于图像去噪的matlab代码-BPFA denoising matlab code for the paper nonparametric bayesian dictionary learning for analysis of noisy and incomplete images download http://www.ee.duke/~mzl/Results/BPFAImage/.
BOVW_Class_DEMO
- Matlab实现BOVW模型，特征提取采用SIFT算法，字典学习采用k-means聚类学习，数据集采用UCM21类分类信息-Matlab achieve BOVW model, feature extraction algorithm using SIFT, dictionary learning using k-means clustering, data collection using UCM21 class category
MP
- MP算法代码 作为对信号进行稀疏分解的方法之一，将信号在完备字典库上进行分解。(MP algorithm as one of the sparse decompose method ,make the single decomposed in a dictionary library)
新建文件夹 (2)
- 字典学习。比如一个向量，是k维的，我现在有一个k*n的字典，其中n>>k，所谓的字典学习，就是在这包含n个向量的字典当中寻找一个线性表示可以表示出当前这个k维的向量。之所以称为“稀疏表示”，因为一般n大于k，比如n=512,k=64。这时候你的字典一定是一个Redundant（冗余的，过剩的）的。因此你的表示里面一定有很多系数为0，因而被称作稀疏表示。 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
Indian
- 使用基于词典的稀疏表示高光谱图像分类,多任务联合稀疏表示和逐步MRF优化的高光谱图像分类(Dictionary-based sparse representation hyperspectral image classification, multi-task joint sparse representation and stepwise MRF optimized hyperspectral image classification)
ETH-Image-Inpainting-master
- 这个文件描述了我们用来获取结果的MATLAB文件， 以及如何再现它们的说明。文件列表包括：buildDictionary.m dictionary.mat get_degrees inPainting.m OMP.m overDCTdict.m overlap_col2im.m overlap_im2col.m peel_mask.m SMP.m(This file describes matlab files that we used to obtain our re