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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 42, Iss. 23 — Aug. 10, 2003
  • pp: 4688–4708

Polynomial Distance Classifier Correlation Filter for Pattern Recognition

Mohamed Alkanhal and B. V. K. Vijaya Kumar  »View Author Affiliations


Applied Optics, Vol. 42, Issue 23, pp. 4688-4708 (2003)
http://dx.doi.org/10.1364/AO.42.004688


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Abstract

We introduce what is to our knowledge a new nonlinear shift-invariant classifier called the polynomial distance classifier correlation filter (PDCCF). The underlying theory extends the original linear distance classifier correlation filter [Appl. Opt. 35, 3127 (1996)] to include nonlinear functions of the input pattern. This new filter provides a framework (for combining different classification filters) that takes advantage of the individual filter strengths. In this new filter design, all filters are optimized jointly. We demonstrate the advantage of the new PDCCF method using simulated and real multi-class synthetic aperture radar images.

© 2003 Optical Society of America

OCIS Codes
(100.4550) Image processing : Correlators
(100.5010) Image processing : Pattern recognition
(100.6740) Image processing : Synthetic discrimination functions

Citation
Mohamed Alkanhal and B. V. K. Vijaya Kumar, "Polynomial Distance Classifier Correlation Filter for Pattern Recognition," Appl. Opt. 42, 4688-4708 (2003)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-42-23-4688


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