Spectral approach to classification based on generalized unconditional tests

Karen O. Egiazarian; Jaakko T. Astola; Sos S. Agaian

doi:10.1117/12.206660

21 April 1995 Spectral approach to classification based on generalized unconditional tests

Karen O. Egiazarian, Jaakko T. Astola, Sos S. Agaian

Proceedings Volume 2501, Visual Communications and Image Processing '95; (1995) https://doi.org/10.1117/12.206660
Event: Visual Communications and Image Processing '95, 1995, Taipei, Taiwan

Abstract

Spectral approach to distribution-free classification is presented. The discriminant function is based on generalized unconditional tests. The main steps of the algorithms are: (1) finding a set of deadlock generalized tests, (2) computing a local discriminant function for each such a test, and (3) performing the actual classification of the observed pattern into a class. The spectral algorithms involve computation of the Walsh and Reed-Muller (conjunctive) spectra using fast algorithms.

Citation Download Citation

Karen O. Egiazarian, Jaakko T. Astola, and Sos S. Agaian "Spectral approach to classification based on generalized unconditional tests", Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); https://doi.org/10.1117/12.206660

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