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Case study of binary and ternary synthetic discriminant function filters with similar in-class and out-of-class imagesA simulation study is reported of the performance of two designs of ternary synthetic discriminant function (SDF) filters. The filters are compared to binary SDFs in terms of the probability of correct identification P(ID) between in-class and out-of-class image sets. Compared to binary synthetic discriminant function (BSDF) filters, both ternary SDF filters designs offer improved performance in P(ID) and thus allow extension of the maximum filter direction range when evaluated in the presence of white image noise. Larger distortion range filters translate to fewer correlations required to perform image identification, and thus higher system speed. The TSDF(SNR) filters had the highest of system performance, while TSDF(d) filters were able to improve discrimination to a degree, but their optimal designs had essentially the same SNR performance as the BSDF filters.
Document ID
19930053060
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Downie, John D.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 16, 2013
Publication Date
March 1, 1993
Publication Information
Publication: Optical Engineering
Volume: 32
Issue: 3
ISSN: 0091-3286
Subject Category
Cybernetics
Accession Number
93A37057
Funding Number(s)
PROJECT: RTOP 506-59-31
Distribution Limits
Public
Copyright
Other

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