搜索资源列表
Tetrolet_Transform
- Tetrolet变换的原代码,一种稀疏表示的小波变换,由haar变换改进得到-Tetrolet transform the original code, a sparse representation of the wavelet transform, haar transform improved
KSVD
- ksvd算法的代码,可以通过训练字典,从而实现对数据的稀疏表示。-ksvd algorithm code, through training dictionary in order to achieve the sparse representation of the data.
omp
- omp算法,该编码通俗易懂,应用简单。用于求压缩感知中,在字典D已知的前提下,一个信号在该字典上的稀疏表示。-omp algorithm, and compressed sensing, sparse representation of a signal in the dictionary in the dictionary D known premise.
WT-OMPmatrix
- 对图像进行压缩感知,通过构造小波正交变换矩阵进行稀疏表示,用OMP重构-CS of image based on WT
Wavelet_OMP
- 本程序实现图像LENA的压缩传感,包括图像的稀疏表示,图像重构等等子函数,运行效果良好-The program image LENA compressive sensing, including the sparsity of the image, image reconstruction, and so subfunction running well
smallbox_2.0
- SMALLbox,这个工具箱不仅用来比较各种稀疏表示的解法,而且把字典学习算法也融合了进去-SMALLbox, the toolbox not only be used to compare various sparse representation of the solution, and the dictionary learning algorithm also combines into
MEland_SparseRepresentation
- 压缩感知稀疏表示领域大牛M.Eland写的书,非常值得一看,主要是字典构造和稀疏表示方面的问题。-A great book form M.Eland ,one of the leaders in Compressed sensing and sparse representation field.It is worth to read.
resource_59304481274953207k
- 本文将稀疏表示用到人脸识别中,取得了较好的识别效果。重要的是特征维数要足够大,稀疏表示可以得到准确计算。-This article sparse representation used in face recognition and achieved good recognition effect. The important feature dimension is large enough, the sparse represent
Solvers
- 稀疏工具箱中的追踪算法集,包括BP,OMP等,这个工具箱是稀疏表示的重要工具。-The sparse toolbox tracking algorithm set,you can apply it in image denoise.This is one part of Sparse solver packages.
face-recognition
- 稀疏表示人脸分类与识别,Mayi人脸分类识别框架,识别率非常高-sparse represention for face recognition
Wavelet_SP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为SP算法,对256*256的lena图处理,比较原图和SP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix
Wavelet_SL0
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为SL0算法,对256*256的lena图处理,比较原图和SL0算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random ma
Wavelet_ROMP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为ROMP算法,对256*256的lena图处理,比较原图和ROMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random
Wavelet_OMP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为OMP算法,对256*256的lena图处理,比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random ma
Wavelet_IRLS
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为ILRS算法,对256*256的lena图处理,比较原图和IRLS算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random mat
shearlet_toolbox(1)
- 这个程序包是矩阵的稀疏表示,适合用于图像处理,简单易懂-This package is a sparse matrix suitable for image processing, simple and easy to understand
SRC_AR_showversion
- 基于稀疏表示的人脸识别算法,是核心算法的演示版本-Face recognition algorithm based on sparse representation is the demo version of the core algorithm
SPARSE
- 用matlab实现的基于稀疏表示的人脸识别方法。其中解稀疏表示时,包含了各种方法。-Using matlab face recognition method based on sparse representation. Solution of the sparse representation, contains a variety of methods.
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 t
Elad-ksvd-matlab-toolbox
- 稀疏表示,字典学习,KSVD算法,matlab版-Sparse representation dictionary learning, KSVD algorithm, matlab