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Proceedings Paper

Local decomposition of invariant lattice transforms
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Paper Abstract

Lattice transformations are a class of nonlinear image processing transforms that include mathematical morphology transforms as a subclass. By using a matrix representation lattice transforms may apply results established in minimax algebra a matrix algebra originally developed for operations research. This paper presents a strong decomposition technique for a translation invariant template that is a lattice transform using a minimax matrix approach. The factors of the decomposition correspond to variant templates. This method is particularly suited for implementation on multiple-instruction multiple-data (MIMD) architectures. Since the minimax algebra is a subalgebra of the Air Force image algebra which in turn encompasses mathematical morphology this technique provides another tool for template decomposition which in particular can be applied to morphology transforms.

Paper Details

Date Published: 1 November 1990
PDF: 12 pages
Proc. SPIE 1350, Image Algebra and Morphological Image Processing, (1 November 1990); doi: 10.1117/12.23611
Show Author Affiliations
Jennifer L. Davidson, Iowa State Univ. (United States)


Published in SPIE Proceedings Vol. 1350:
Image Algebra and Morphological Image Processing
Paul D. Gader, Editor(s)

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