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自己编写的稀疏去噪代码
- 先使用K-means聚类算法将图像分为几个类，然后针对每一类分别Ksvd字典训练和稀疏表示，进行去噪
OSDL_Package
- 高维字典学习，可以处理高维信号或者是大型数据集，训练速度快-high dimension dictionary learning
Super-resolution
- 实现联合字典训练的超分辨率重建算法，通过分别训练高分辨率字典和低分辨率字典-1. The demo code is for upscaling factor of 2. For larger magnification factors, run the function ScSR.m multiple times. Note the code is a little different what presented in the TIP10 paper. Please find the p
reg_sparse_coding
- 稀疏重建联合字典训练用于超分辨率重建，基于正则化框架-Dictionary sparse reconstruction joint training for super-resolution reconstruction, based on the regular framework
train_coupled_dict
- 用于对所获取的图像块做联合字典的稀疏表示训练-For the acquired image block sparse representation of the dictionary to do joint training
OMPerr
- 图像处理中稀疏表示中用于实时更新字典、稀疏系数-Image processing sparse representation for real-time update the dictionary, sparse coefficient
DLTG_v2
- 基于字典学习的动态的MRI欠采样的图像重建，分为实部与虚部 分别重建-dynamic under-sampling MRI image reconstruction based dictionary learning ,whic is divided into real and imaginary part
SP-TrainDictionary-ksvd--demo
- 图像处理，稀疏表示，字典去噪，ksvd，人脸识别-Image processing, sparse representation, dictionary denoising, KSVD, face recognition
KSVD_Matlab_ToolBox
- 基于KSVD算法的图像去噪算法，稀疏表示，字典学习，OMP算法，基于DCT字典的图像去噪，demo可以直接运行。-Image denoising by KSVD algorithm，spare representation，dictionary learning，OMP algorithm，DCT dictionary
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
LKDL_Package
- 该程序包是一种新的算法（LKDL），该算法是基于核的字典学习，能够很好的应用于离线字典学习的预处理阶段。-The work presented in this paper describes a new approach for incorporating kernels into dictionary learning，termed Linearized Kernel Dictionary Learning (LKDL)，can be seamlessly applied as a pre
DPL-CNN
- 最新的基于卷积神经网络和字典对分类器的图像识别与分类算法资料-Image recognition and classification algorithm based on convolution neural network and dictionary classifier
CSR_Denoising
- 该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）-It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the
SpectrumRecongnize
- 高光谱识别程序。可以改变字典长度进行多尺度识别，识别时，利用重构误差改变字典长度，通过高斯变换得到多尺度信息进行识别-Hyperspectral recognition program. Can change the length of the dictionary for multi-scale recognition, recognition, the use of reconstruction error to change the dictionary length, through t
稀疏分解图像去噪
- 基于稀疏字典和稀疏编码的图像去噪算法，基于低秩约束的高光谱条纹噪声去除，包含论文及代码(Based on sparse dictionary and sparse coding image denoising algorithm, based on low rank constraints of hyperspectral fringe noise removal, including papers and code)
归档
- 此函数用PCD算法解决压缩感知（构造冗余字典用于图像修复）(This function uses the PCD algorithm to solve compressed sensing (redundant dictionaries are constructed for image inpainting))
NSSR_HSI_SR
- 使用贝塔过程进行联合字典学习进而进行超分辨重建(use beta process joint dictionary learning to image super-resolution)
Dual_Dic_SR
- 通过进行双字典学习来完成单幅影像超分辨率重建(use dual dictionary learning to single image super resolution)
BPFA_Denoising
- 利用非参数贝叶斯字典学习模型进行图像稀疏表示(use non-parametric-bayesian-dictionary-learning-for-sparse-image-representations)
ompbox9
- 一种经典的用来更新稀疏字典系数的方法正交匹配追踪法(A classical method for updating sparse dictionary coefficients -- orthogonal matching pursuit)