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A statistical approach to the problem of restoring damaged and contaminated images
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Everitt, Richard G. and Glendinning, Richard H. (2009) A statistical approach to the problem of restoring damaged and contaminated images. Pattern Recognition, 42 (1). pp. 115-125. doi:10.1016/j.patcog.2008.06.009 ISSN 0031-3203.
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Official URL: https://doi.org/10.1016/j.patcog.2008.06.009
Abstract
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: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||
Journal or Publication Title: | Pattern Recognition | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 0031-3203 | ||||||||
Official Date: | January 2009 | ||||||||
Dates: |
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Volume: | 42 | ||||||||
Number: | 1 | ||||||||
Page Range: | pp. 115-125 | ||||||||
DOI: | 10.1016/j.patcog.2008.06.009 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
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