DocumentCode
2155446
Title
Adaptive reconstruction method of missing textures based on perceptually optimized algorithm
Author
Ogawa, Takahiro ; Haseyama, Miki
Author_Institution
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
fYear
2011
fDate
22-27 May 2011
Firstpage
1157
Lastpage
1160
Abstract
This paper presents an adaptive reconstruction method of missing textures based on structural similarity (SSIM) index. The proposed method firstly performs SSIM-based selection of the optimal known local textures to adaptively obtain subspaces for reconstructing missing textures. Furthermore, from the selected known textures, the missing texture reconstruction maximizing the SSIM index is performed. In this approach, the non-convex maximization problem is reformulated as a quasi convex problem, and the adaptive reconstruction of the missing textures becomes feasible. Experimental results show impressive improvement of the proposed method over previously reported reconstruction methods.
Keywords
concave programming; image reconstruction; image texture; adaptive reconstruction method; local textures; missing textures; nonconvex maximization problem; perceptually optimized algorithm; quasiconvex problem; structural similarity index; Equations; Image reconstruction; Image restoration; Indexes; Mathematical model; Pixel; Reconstruction algorithms; Image restoration; image quality assessment; image texture analysis; interpolation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location
Prague
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2011.5946614
Filename
5946614
Link To Document