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Proceedings Paper

K-factor image factorization
Author(s): John L. Johnson; Jaime R. Taylor
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Paper Abstract

A new computational paradigm is introduced. Other image representation such as Fourier transforms and wavelet decompositions depend on linear superposition of basis functions. The k-factor image factorization reduces an image into a finite or infinite set of contrast-ordered images whose joint product reproduces the original image. It is experimentally found that shadows and noise often fall into factors disjoint from the 'pure' image. The analytical foundations of the k-factor method are given, followed by full factorizations and reconstructions, and future research directions are described that include shadow removal, speckle reduction, medical and military image analysis, and commercial applications.

Paper Details

Date Published: 9 March 1999
PDF: 9 pages
Proc. SPIE 3715, Optical Pattern Recognition X, (9 March 1999); doi: 10.1117/12.341298
Show Author Affiliations
John L. Johnson, U.S. Army Aviation and Missile Command (Germany)
Jaime R. Taylor, Austin Peay State Univ. (United States)


Published in SPIE Proceedings Vol. 3715:
Optical Pattern Recognition X
David P. Casasent; Tien-Hsin Chao, Editor(s)

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