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Smooth incomplete matrix factorization and its applications in image/video denoising

文献类型：期刊论文

作者Dong, Qiulei1; Li, Lu2
刊名NEUROCOMPUTING
出版日期2013-12-25
卷号122页码:458-469
关键词Low-rank matrix factorization Missing elements Discretized Laplacian smoothing Image/video denoising
英文摘要Low-rank matrix factorization with missing elements has many applications in computer vision. However, the original model without taking any prior information, which is to minimize the total reconstruction error of all the observed matrix elements, sometimes provides a physically meaningless solution in some applications. In this paper, we propose a regularized low-rank factorization model for a matrix with missing elements, called Smooth Incomplete Matrix Factorization (SIMF), and exploit a novel image/video denoising algorithm with the SIMF. Since data in many applications are usually of intrinsic spatial smoothness, the SIMF uses a 2D discretized Laplacian operator as a regularizer to constrain the matrix elements to be locally smoothly distributed. It is formulated as two optimization problems under the l(1) norm and the Frobenius norm, and two iterative algorithms are designed for solving them respectively. Then, the SIMF is extended to the tensor case (called Smooth Incomplete Tensor Factorization, SITF) by replacing the 2D Laplacian by a high-dimensional Laplacian. Finally, an image/video denoising algorithm is presented based on the proposed SIMF/SITF. Extensive experimental results show the effectiveness of our algorithm in comparison to other six algorithms. (C) 2013 Elsevier B.V. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]LOW-RANK MATRIX ; MISSING DATA ; ALGORITHMS ; MOTION ; REGULARIZATION
收录类别SCI
语种英语
WOS记录号WOS:000325590200047
源URL[http://ir.ia.ac.cn/handle/173211/2990]  
专题自动化研究所_模式识别国家重点实验室_机器人视觉团队
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China
推荐引用方式
GB/T 7714		 Dong, Qiulei,Li, Lu. Smooth incomplete matrix factorization and its applications in image/video denoising[J]. NEUROCOMPUTING,2013,122:458-469.
APA Dong, Qiulei,&Li, Lu.(2013).Smooth incomplete matrix factorization and its applications in image/video denoising.NEUROCOMPUTING,122,458-469.
MLA Dong, Qiulei,et al."Smooth incomplete matrix factorization and its applications in image/video denoising".NEUROCOMPUTING 122(2013):458-469.

入库方式： OAI收割

来源：自动化研究所

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