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
fDate :
Sept. 30 2012-Oct. 3 2012
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;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467210