Share Email Print

Proceedings Paper

Minimax Techniques For Optimizing Non-Linear Image Algebra Transforms
Author(s): J. L. Davidson
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

It has been well established that the Air Force Armament Technical Laboratory (AFATL) image algebra is capable of expressing all linear transformations [7]. The embedding of the linear algebra in the image algebra makes this possible. In this paper we show a relation of the image algebra to another algebraic system called the minimax algebra. This system is used extensively in economics and operations research, but until now has not been investigated for applications to image processing. The relationship is exploited to develop new optimization methods for a class of non-linear image processing transforms. In particular, a general decomposition technique for templates in this non-linear domain is presented. Template decomposition techniques are an important tool in mapping algorithms efficiently to both sequential and massively parallel architectures.

Paper Details

Date Published: 30 August 1989
PDF: 12 pages
Proc. SPIE 1098, Aerospace Pattern Recognition, (30 August 1989); doi: 10.1117/12.960431
Show Author Affiliations
J. L. Davidson, University of Florida (United States)

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

© SPIE. Terms of Use
Back to Top