4.6 Article Proceedings Paper

Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA)

期刊

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
卷 19, 期 3, 页码 340-358

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.acha.2005.03.005

关键词

basis pursuit; total variation; sparse representation; cartoon; texture; inpainting

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This paper describes a novel inpainting algorithm that is capable of filling in holes in overlapping texture and cartoon image layers. This algorithm is a direct extension of a recently developed sparse-representation-based image decomposition method called MCA (morphological component analysis), designed for the separation of linearly combined texture and cartoon layers in a given image (see [J.-L. Starck, M. Elad, D.L. Donoho, Image decomposition via the combination of sparse representations and a variational approach, IEEE Trans. Image Process. (2004), in press] and [J.-L. Starck, M. Elad, D.L. Donoho, Redundant multiscale transforms and their application for morphological component analysis, Adv. Imag. Electron Phys. (2004) 132]). In this extension, missing pixels fit naturally into the separation framework, producing separate layers as a by-product of the inpainting process. As opposed to the inpainting system proposed by Bertalmio et al., where image decomposition and filling-in stages were separated as two blocks in an overall system, the new approach considers separation. hole-filling, and denoising as one unified task. We demonstrate the performance of the new approach via several examples. (c) 2005 Elsevier Inc. All rights reserved.

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