K-factor image factorization

John L. Johnson; Jaime R. Taylor

doi:10.1117/12.341298

9 March 1999 K-factor image factorization

John L. Johnson, Jaime R. Taylor

Proceedings Volume 3715, Optical Pattern Recognition X; (1999) https://doi.org/10.1117/12.341298
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

John L. Johnson and Jaime R. Taylor "K-factor image factorization", Proc. SPIE 3715, Optical Pattern Recognition X, (9 March 1999); https://doi.org/10.1117/12.341298

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