DocumentCode
3408064
Title
Rank minimization approach to image inpainting using null space based alternating optimization
Author
Takahashi, Tatsuro ; Konishi, Katsumi ; Furukawa, Toshihiro
Author_Institution
Grad. Sch. of Eng., Tokyo Univ. of Sci., Tokyo, Japan
fYear
2012
fDate
Sept. 30 2012-Oct. 3 2012
Firstpage
1717
Lastpage
1720
Abstract
This paper proposes a novel image inpainting based on the matrix rank minimization. Assuming that an image can be modeled by the autoregressive (AR) model, this paper formulates the image inpainting problem as the signal recovery problem of an AR model. The main result of this paper is to reformulate this problem as the matrix rank minimization and to provide an inpainting algorithm based on the null space based alternating optimization (NSAO) algorithm. Numerical examples show that the proposed algorithm recovers missing pixels efficiently.
Keywords
autoregressive processes; image processing; image texture; matrix algebra; minimisation; AR model; NSAO algorithm; autoregressive model; image inpainting algorithm; image inpainting problem; matrix rank minimization approach; null space based alternating optimization algorithm; signal recovery problem; Approximation algorithms; Computational modeling; Linear programming; Minimization; Null space; Numerical models; Optimization; AR modeling; image inpainting; matrix rank minimization; matrix recovery; texture recovery;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1522-4880
Print_ISBN
978-1-4673-2534-9
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2012.6467210
Filename
6467210
Link To Document