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Binary Sparse Representation Based on Arbitrary Quality Metrics and Its Applications

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/72332

Title: Binary Sparse Representation Based on Arbitrary Quality Metrics and Its Applications
Authors: Ogawa, Takahiro Browse this author →KAKEN DB
Takahashi, Sho Browse this author →KAKEN DB
Wada, Naofumi Browse this author
Tanaka, Akira Browse this author →KAKEN DB
Haseyama, Miki Browse this author →KAKEN DB
Keywords: image approximation
binary sparse representation
image quality metrics
visual saliency
Issue Date: Nov-2018
Publisher: 電子情報通信学会
Journal Title: IEICE transactions on fundamentals of electronics, communications and computer sciences
Issue: 11
Start Page: 1776
End Page: 1785
Publisher DOI: 10.1587/transfun.E101.A.1776
Abstract: Binary sparse representation based on arbitrary quality metrics and its applications are presented in this paper. The novelties of the proposed method are twofold. First, the proposed method newly derives sparse representation for which representation coefficients are binary values, and this enables selection of arbitrary image quality metrics. This new sparse representation can generate quality metric-independent subspaces with simplification of the calculation procedures. Second, visual saliency is used in the proposed method for pooling the quality values obtained for all of the parts within target images. This approach enables visually pleasant approximation of the target images more successfully. By introducing the above two novel approaches, successful image approximation considering human perception becomes feasible. Since the proposed method can provide lower-dimensional subspaces that are obtained by better image quality metrics, realization of several image reconstruction tasks can be expected. Experimental results showed high performance of the proposed method in terms of two image reconstruction tasks, image inpainting and super-resolution.
Rights: copyright©2018 IEICE
Relation: http://search.ieice.org/
Type: article
URI: http://hdl.handle.net/2115/72332
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 小川 貴弘

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