Search Results - low-rank regularized group sparse coding

Image Restoration via Reconciliation of Group Sparsity and Low-Rank Models by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhou, Jiantao, Zhu, Ce

“… In this paper, we propose a novel NSS-based sparsity model, namely, low-rank regularized group sparse coding (LR-GSC…”
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Structural Smoothing Low-Rank Matrix Restoration Based on Sparse Coding and Dual-Weighted Model by Wu, Jiawei, Wang, Hengyou

“… Low-rank regularized group sparse coding (LR-GSC) reduces this gap by imposing low-rankness on the group sparse coefficients…”
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Reconciliation Of Group Sparsity And Low-Rank Models For Image Restoration by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhou, Jiantao, Zhu, Ce

“… In this paper, we propose a novel NSS-based sparsity model, namely low-rank regularized group sparse coding (LR-GSC…”
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Medical Image Denoising Algorithm Based on Sparse Nonlocal Regularized Weighted Coding and Low Rank Constraint by Yuan, Quan, Peng, Zhenyun, Chen, Zhencheng, Guo, Yanke, Yang, Bin, Zeng, Xiangyan

“… The existing denoising algorithm of weight coding based on sparse nonlocal regularization, which can simultaneously remove AWGN and impulse noise, is plagued by the problems of incomplete noise…”
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Low-Rank Regularized Joint Sparsity for Image Denoising by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhou, Jiantao, Zhu, Ce

“… To simultaneously exploit the low-rank and JS priors, we propose a novel low-rank regularized joint sparsity model, dubbed LRJS, to enhance the dependency (i. e., low-rankness…”
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A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem by Montoya-Martínez, Jair, Artés-Rodríguez, Antonio, Pontil, Massimiliano, Hansen, Lars Kai

“… The structured sparse-low-rank structure is enforced by minimizing a regularized functional that includes the ℓ…”
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A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem: Doc 661 by Montoya-martínez, Jair, Artés-rodríguez, Antonio, Pontil, Massimiliano, Hansen, Lars Kai

“… The structured sparse-low-rank structure is enforced by minimizing a regularized functional that includes the ^sub 21…”
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Nonconvex L1/2- regularized nonlocal self-similarity denoiser for compressive sensing based CT reconstruction by Li, Yunyi, Jiang, Yiqiu, Zhang, Hengmin, Liu, Jianxun, Ding, Xiangling, Gui, Guan

“… In this paper, we develop an L1/2-regularized nonlocal self-similarity (NSS) denoiser based CT reconstruction model, which combines with low-rank approximation and group sparse coding (GSC) framework…”
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High-quality Image Restoration Using Low-Rank Patch Regularization and Global Structure Sparsity by Mingli Zhang, Desrosiers, Christian

“… Enforcing this structural information to be sparse can thus reduce the occurrence of reconstruction artifacts…”
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A robust mixed error coding method based on nonconvex sparse representation by Lv, Wei, Zhang, Chao, Li, Huaxiong, Wang, Bo, Chen, Chunlin

“… In specific, we use weighted ℓ2-norm based robust coding to characterize the sparse noise in images, and weighted matrix nuclear norm to characterize the low-rank noise…”
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Nonconvex L 1 / 2 - regularized nonlocal self-similarity denoiser for compressive sensing based CT reconstruction by Li, Yunyi, Jiang, Yiqiu, Zhang, Hengmin, Liu, Jianxun, Ding, Xiangling, Gui, Guan

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Nonconvex \({{L_ {{1/2}}}} \)-Regularized Nonlocal Self-similarity Denoiser for Compressive Sensing based CT Reconstruction by Li, Yunyi, Jiang, Yiqiu, Zhang, Hengmin, Liu, Jianxun, Ding, Xiangling, Guan Gui

“… In this paper, we develop a \({{L_ {{1/2}}} \)-regularized nonlocal self-similarity (NSS) denoiser for CT reconstruction problem, which integrates low-rank approximation with group sparse coding (GSC) framework…”
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Structured sparse-low rank matrix factorization for the EEG inverse problem by Montoya-Martinez, Jair, Artes-Rodriguez, Antonio, Pontil, Massimiliano

“… We propose a new method based on the factorization of the BES as a product of a sparse coding matrix and a dense latent source matrix…”
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Nonconvex relaxation based matrix regression for face recognition with structural noise and mixed noise by Zhang, Hengmin, Yang, Jian, Qian, Jianjun, Luo, Wei

“…For face recognition, sparse coding based classification methods have demonstrated the inspiring attraction in dealing with the pixel-level based sparse or gaussian noise, and nuclear norm based matrix regression (NMR…”
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