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A statistical approach to the problem of restoring damaged and contaminated images

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Everitt, R. and Glendinning, R. H. (2009) A statistical approach to the problem of restoring damaged and contaminated images. Pattern Recognition, 42 (1). pp. 115-125. ISSN 0031-3203

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To link to this article DOI: 10.1016/j.patcog.2008.06.009

Abstract/Summary

We address the problem of automatically identifying and restoring damaged and contaminated images. We suggest a novel approach based on a semi-parametric model. This has two components, a parametric component describing known physical characteristics and a more flexible non-parametric component. The latter avoids the need for a detailed model for the sensor, which is often costly to produce and lacking in robustness. We assess our approach using an analysis of electroencephalographic images contaminated by eye-blink artefacts and highly damaged photographs contaminated by non-uniform lighting. These experiments show that our approach provides an effective solution to problems of this type.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics > Applied Statistics
ID Code:29091
Publisher:Elsevier

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