搜索资源列表
DictionaryLearning
- 字典学习训练，利用学习训练字典达到较好的稀疏分解效果
focuss-cndl.zip
- focuss算法 关于图像稀疏性分解中字典学习的经典算法 和大家一同分享 ,focuss algorithm on the sparse image decomposition in the dictionary of the classical learning algorithm and we share
Compression-sensing
- 压缩传感理论，用K-SVD算法训练字典，过完备字典-Compression sensing theory, SVD algorithm with K- had complete training dictionary, dictionary
ImageFusionGlobal
- 用正交匹配跟踪的方法实现图像融合，通过训练得到字典-image fuse
k_svd
- k-svd算法m代码.用于形成冗余字典，对图像进行稀疏分解-m k-svd algorithm code used to create a redundant dictionaries, sparse decomposition of images
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.
Binarization
- 数字图像处理，用大津算法对图像进行二值化处理，VC/MFC实现。-Digital image processing, with the Otsu algorithm to the image binarization, VC/MFC implementation. 朗读显示对应的拉丁字符的拼音 字典- 查看字典详细内容 翻译以下任意网站Nord-Cinema-法国Venezuela Tuya-西班牙语Museo del Prado-Digital image processin
work6
- 实现图像的huffman编码，并得到生成矩阵和字典-Huffman realize image coding, and get a generator matrix and dictionaries
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
overcomplete
- 收集的几篇关于稀疏性号冗余字典建立的中文文献，对初学者很有参考价值。-Collection of several dictionaries on the sparsity of the establishment of redundant number of Chinese literature, a good reference for beginners.
@partialDCT
- 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.
fusedLasso
- 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.
tree
- 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.
Fusion
- 用OPM的方法实现图像融合，训练得到了正交匹配跟踪字典-fuse image
K-SVD_and_W_KSVD_Sparse_Representation
- 通过字典学习更新的方法，对图像信号进行稀疏化分解(Through the method of learning and updating the dictionary, the image signals are sparse decomposed)
稀疏融合
- 利用DCT字典对图形进行稀疏表示，实现两幅图像的融合(Using the DCT dictionary to sparse representation of the graphics to achieve the fusion of two images)
Facial Expression Recognition
- 源码简介：ksvd字典学习进行表情识别 对比ksvd字典学习 与最近邻算法对比输出失败率用ksvd字典学习进行表情识.(Source code introduction: ksvd dictionary learning for expression recognition contrast ksvd dictionary learning and nearest neighbor algorithm comparison output failure rate using ksvd dict
图像修复
- 应用DCT字典和KSVD学习字典，对图像进行简单的修复，可行性较高，速度不是很快。(Simple image restoration is feasible and not very fast.)
14、字典学习
- 经典的KSVD图像字典学习，matlab 代码，有注释，亲测可用(The classic KSVD image dictionary learning, matlab code, include notes, test available)