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Paper Abstract and Keywords
Presentation 2019-06-13 16:25
[Invited Talk] Sparse/low-rank Modeling for Image Processing
Seisuke Kyochi (The Univ. of Kitakyushu)
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents fundamental tools for image recovery by convex optimization and introduces some case study from the author’s related works. During the image acquisition, images are often corrupted by many kinds of degradation, such as noise, blur caused by incorrect focus or handshaking. In image recovery framework, each process of degradation is mathematically modeled as a regularizer and integrated into the cost function. Finally, by solving the inverse problem, the desired image is estimated. For accurate image recovery, a suitable regularizer should be designed. In this paper, some convex regularizers based on sparsity and low-rankness are presented and shown their effectiveness in experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) Image recovery / Convex optimization / Sparse modeling / Low-rank modeling / / / /  
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Conference Information
Committee IEICE-SIS IPSJ-AVM 3DMT  
Conference Date 2019-06-13 - 2019-06-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukue Culture Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Enbedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To IEICE-SIS 
Conference Code 2019-06-SIS-AVM-3DIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Sparse/low-rank Modeling for Image Processing 
Sub Title (in English)  
Keyword(1) Image recovery  
Keyword(2) Convex optimization  
Keyword(3) Sparse modeling  
Keyword(4) Low-rank modeling  
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1st Author's Name Seisuke Kyochi  
1st Author's Affiliation The University of Kitakyushu (The Univ. of Kitakyushu)
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Speaker Author-1 
Date Time 2019-06-13 16:25:00 
Presentation Time 60 minutes 
Registration for IEICE-SIS 
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Volume (vol) vol.43 
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