Z Jian, Z Debin, G Wen, Group-based sparse representation for image restoration. IEEE Trans. Image Process. 23(8), 3336-3351 (2014)ZHANG J, ZHAO D, GAO W. Group-based sparse representation for image restoration [J]. IEEE transactions on image processing, 2014, 8(23): 3336-33...
Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse co...
Image deblocking using group-based sparse representation and quantization constraint prior 来自 学术范 喜欢 0 阅读量: 112 作者:Z Jian,S Ma,Y Zhang,G Wen 摘要: To alleviate the conflict between bit reduction and quality preservation, deblocking as a post-processing strategy is an attractive and ...
Unsupervised Band Selection Based on Group-Based Sparse RepresentationBand selection (BS) is one of the important topics in hyperspectral image data analysis. How to search the representative bands that can effectively represent the image with lower inter-band......
Group-based sparse representationNonlocal total variationJoint regularizationSplit Bregman iterationCompressive sensing (CS) has recently drawn considerable attentions in signal and image processing communities as a joint sampling and compression approach. Generally, the image CS reconstruction can be formulated...
Group-based Sparse Representation for Image Restoration (Matlab Code) These MATLAB programs implement the image restoration algorithms via group-based sparse representation (GSR) modeling as described in paper: Jian Zhang, Debin Zhao, Wen Gao, "Group-based Sparse Representation for Image Restoration",...
Recent advances have suggested that group sparse representation based models, which exploit nonlocal self-similarity prior, lead to superior results in image CS recovery. In this paper, we propose a CS recovery method via group sparse representation with nonconvex LLp norm regularization (GSR-LLp)....
Group-based sparse representation for image compressive sensing reconstruction with non-convex regularization - ScienceDirect Patch-based sparse representation modeling has shown great potential in image compressive sensing (CS) reconstruction. However, this model usually suffers ... Zhiyuan Zha a,Xinggan ...
In this paper, a sparse representation-based intuitionistic fuzzy clustering (SRIFC) approach is presented for solving the large-scale decision making (LSDM) problem. It consists of two algorithms: the sparse representation-based intuitionistic fuzzy clustering-exactly precision algorithm (which is presen...
Group-based sparse representation for image compressive sensing reconstruction with non-convex regularization. Neurocomputing 2018, 296, 55–63. [Google Scholar] [CrossRef] [Green Version] Ren, X.; Bai, Y.; Jiang, Y. Hybrid spatial model for fast terahertz imaging. Micromachines 2021, 12, ...