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Proceedings Paper

Models For Natural Clutter In Coherent Imaging
Author(s): J. R. Garside; C. J. Oliver
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Paper Abstract

Many examples of clutter textures in coherent imaging demonstrate K-distributed statistics which result from a gamma-distributed surface cross-section. Such a surface can be completely described in terms of the average two-point statistics (eg the autocorrelation function, ACF) of the process. We compare simulation methods based on such a noise model with a direct model in which we attempt to represent the underlying properties of the surface. A particular example of random woodland clutter is selected in which case this direct model represents quantities such as tree position, size distribution, shape, volume scattering properties and the illumination. We demonstrate that this model predicts processes, such as shadowing, directly, unlike the noise models which combine all factors into the global description. However, further work is needed on this approach before the predicted textures resemble the original SAR texture as closely as those generated by the noise model when the intensity ACF of the texture is reproduced.

Paper Details

Date Published: 11 October 1989
PDF: 8 pages
Proc. SPIE 1135, Image Processing III, (11 October 1989); doi: 10.1117/12.961643
Show Author Affiliations
J. R. Garside, Royal Signals and Radar Establishment (UK)
C. J. Oliver, Royal Signals and Radar Establishment (UK)

Published in SPIE Proceedings Vol. 1135:
Image Processing III
Jacques Frank Duvernoy, Editor(s)

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