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Proceedings Paper

A comparison of image inpainting techniques
Author(s): Yaojie Liu; Chang Shu
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Paper Abstract

Image inpainting is an important research topic in the field of image processing. The objective of inpainting is to “guess” the lost information according to surrounding image information, which can be applied in old photo restoration, object removal and demosaicing. Based on the foundation of previous literature of image inpainting and image modeling, this paper provides an overview of the state-of-art image inpainting methods. This survey first covers mathematics models of inpainting and different kinds of image impairment. Then it goes to the main components of an image, the structure and the texture, and states how these inpainting models and algorithms deal with the two separately, using PDE’s method, exemplar-based method and etc. Afterwards sparse-representation-based inpainting and related techniques are introduced. Experimental analysis will be presented to evaluate the relative merits of different algorithms, with the measure of Peak Signal to Noise Ratio (PSNR) as well as direct visual perception.

Paper Details

Date Published: 4 March 2015
PDF: 11 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431M (4 March 2015); doi: 10.1117/12.2178820
Show Author Affiliations
Yaojie Liu, Univ. of Electronic Science and Technology of China (China)
Chang Shu, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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