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Proceedings Paper

Image Algebra And Morphological Template Decomposition
Author(s): Paul Gader; Elizabeth G. Dunn
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Paper Abstract

Development and testing of image processing algorithms for real-time aerospace pattern recognition applications can be extremely time consuming and labor intensive. There is a need to close the gap between high-level software environments and efficient implementations. Image algebra is an algebraic structure designed for image processing that can be used as a basis for a high-level algorithm development environment. Systematic methods for mapping algorithms represented by image algebra statements to specific architectures are being studied. In this paper we discuss template decomposition, a problem encountered in mapping image algebra statements to combinations of parallel and pipeline architectures. In particular, we show that the gray scale morphological template decomposition problem can be viewed as a linear problem, even though morphological transformations are nonlinear. We show how methods for solving linear programming problems and, in particular, the transportation problem can be applied to template decomposition.

Paper Details

Date Published: 30 August 1989
PDF: 12 pages
Proc. SPIE 1098, Aerospace Pattern Recognition, (30 August 1989); doi: 10.1117/12.960432
Show Author Affiliations
Paul Gader, Environmental Research Institute of Michigan (United States)
Elizabeth G. Dunn, University of Wisconsin (United States)

Published in SPIE Proceedings Vol. 1098:
Aerospace Pattern Recognition
Marshall R. Weathersby, Editor(s)

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