Minimax Techniques For Optimizing Non-Linear Image Algebra Transforms

J. L. Davidson

doi:10.1117/12.960431

30 August 1989 Minimax Techniques For Optimizing Non-Linear Image Algebra Transforms

J. L. Davidson

Proceedings Volume 1098, Aerospace Pattern Recognition; (1989) https://doi.org/10.1117/12.960431
Event: SPIE 1989 Technical Symposium on Aerospace Sensing, 1989, Orlando, FL, United States

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.

Citation Download Citation

J. L. Davidson "Minimax Techniques For Optimizing Non-Linear Image Algebra Transforms", Proc. SPIE 1098, Aerospace Pattern Recognition, (30 August 1989); https://doi.org/10.1117/12.960431

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