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Missing Texture Reconstruction Method Based on Perceptually Optimized Algorithm

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/44859

Title: Missing Texture Reconstruction Method Based on Perceptually Optimized Algorithm
Authors: Ogawa, Takahiro Browse this author
Haseyama, Miki Browse this author
Issue Date: 2010
Publisher: Hindawi Publishing Corporation
Journal Title: EURASIP Journal on Advances in Signal Processing
Volume: 2010
Start Page: 208976
Publisher DOI: 10.1155/2010/208976
Abstract: This paper presents a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm. The proposed method utilizes the structural similarity (SSIM) index as a new visual quality measure for reconstructing missing areas. Furthermore, in order to adaptively reconstruct target images containing several kinds of textures, the following two novel approaches are introduced into the SSIM-based reconstruction algorithm. First, the proposed method performs SSIM-based selection of the optimal known local textures to adaptively obtain subspaces for reconstructing missing textures. Secondly, missing texture reconstruction that maximizes the SSIM index in the known neighboring areas is performed. In this approach, the nonconvex maximization problem is reformulated as a quasi convex problem, and adaptive reconstruction of the missing textures based on the perceptually optimized algorithm becomes feasible. Experimental results show impressive improvements of the proposed method over previously reported reconstruction methods.
Rights: http://creativecommons.org/licenses/by/2.0/
Type: article
URI: http://hdl.handle.net/2115/44859
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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