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Yaojie Liu

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Proceedings Article | 4 March 2015 Paper

A comparison of image inpainting techniques

Yaojie Liu, Chang Shu

Proceedings Volume 9443, 94431M (2015) https://doi.org/10.1117/12.2178820

KEYWORDS: Visualization, Image restoration, Associative arrays, Detection and tracking algorithms, Mathematical modeling, Image processing, Image compression, Algorithms, Signal to noise ratio, 3D image reconstruction

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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.

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