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Proceedings Paper

Mitigation of image impairments for multichannel remote sensing data fusion
Author(s): Andriy Kurekin; Alexander N. Dolia; David Marshall; Vladimir Lukin; Kenneth Lever
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Paper Abstract

Whilst for the majority of applications image quality depends on sensor accuracy and principles of image formation, in remote sensing systems information is also degraded by communication errors. To improve image fusion results in the presence of communication and sensor impairments we propose a two-stage approach. Preliminary nonlinear locally-adaptive image processing is applied at the first stage for mitigating impairments produced in image sensors and communication systems, and fusion algorithms are used at the second stage. The efficiency of the proposed algorithms is demonstrated for satellite remote sensing images and simulated data with similar characteristics and distortions. The influence of image distortions and the effectiveness of mitigation are estimated for an image fusion architecture for low-level image classification based on artificial neural networks. Experimental results are presented providing quantitative assessment of the proposed algorithms.

Paper Details

Date Published: 25 May 2005
PDF: 12 pages
Proc. SPIE 5817, Visual Information Processing XIV, (25 May 2005); doi: 10.1117/12.603103
Show Author Affiliations
Andriy Kurekin, Cardiff Univ. (United Kingdom)
Alexander N. Dolia, Univ. of Southampton (United Kingdom)
David Marshall, Cardiff Univ. (United Kingdom)
Vladimir Lukin, National Aerospace Univ. (Ukraine)
Kenneth Lever, Cardiff Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 5817:
Visual Information Processing XIV
Zia-ur Rahman; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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