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Proceedings Paper

Image-algebraic design of multispectral target recognition algorithms
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Paper Abstract

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Paper Details

Date Published: 30 June 1994
PDF: 16 pages
Proc. SPIE 2300, Image Algebra and Morphological Image Processing V, (30 June 1994); doi: 10.1117/12.179193
Show Author Affiliations
Mark S. Schmalz, Univ. of Florida (United States)
Gerhard X. Ritter, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 2300:
Image Algebra and Morphological Image Processing V
Edward R. Dougherty; Paul D. Gader; Michel Schmitt, Editor(s)

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