Structured matrix rank minimization approach to image inpainting

Tomohiro Takahashi, Katsumi Konishi, Toshihiro Furukawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This paper proposes a structured matrix rank minimization approach to a novel image inpainting. We utilize the autoregressive (AR) model to describe the gray level of image, and formulate the image inpainting problem as the signal recovery problem by estimating the model order. This problem is described as the rank minimization problem, which is NP hard in general. To solve the problem approximately, this paper proposes an algorithm utilizing the null space based alternating optimization (NSAO) algorithm. Numerical examples show that the proposed algorithm recovers missing pixels well.

Original languageEnglish
Title of host publication2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
Pages860-863
Number of pages4
DOIs
Publication statusPublished - 16 Oct 2012
Event2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012 - Boise, ID, United States
Duration: 5 Aug 20128 Aug 2012

Publication series

NameMidwest Symposium on Circuits and Systems
ISSN (Print)1548-3746

Conference

Conference2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
CountryUnited States
CityBoise, ID
Period5/08/128/08/12

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Takahashi, T., Konishi, K., & Furukawa, T. (2012). Structured matrix rank minimization approach to image inpainting. In 2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012 (pp. 860-863). [6292156] (Midwest Symposium on Circuits and Systems). https://doi.org/10.1109/MWSCAS.2012.6292156