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

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 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
URI	https://reading-clone.eprints-hosting.org/id/eprint/29091
Identification Number/DOI	10.1016/j.patcog.2008.06.009
Refereed	Yes
Divisions	No Reading authors. Back catalogue items Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
Publisher	Elsevier
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