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Proceedings Paper

Wiener filter: synthetic discriminant function for target identification
Author(s): Christopher R. Chatwin; Ruikang K. Wang; Rupert C. D. Young
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Paper Abstract

The Wiener filter, which has been used extensively for image restoration and signal processing, is employed for robust optical pattern recognition and classification. The Wiener filter is formulated to incorporate the in-class image and the out-of-class noise image into a single step filter construction. It is compared with the classical matched filter (CMF) and phase-only filter (POF), demonstrating a superior discrimination capability. The Wiener filter is incorporated into a synthetic discriminant function (SDF); correlation results show that it is tolerant to image distortion. With a 30 degree out-of-plane rotation between training set images, the Wiener filter-SDF achieves a 100% success rate in discriminating one-class of images from another. The CMF-SDF and POF-SDF fail to achieve 100% discrimination even at rotation increments of 15 degrees.

Paper Details

Date Published: 5 July 1995
PDF: 20 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213056
Show Author Affiliations
Christopher R. Chatwin, Glasgow Univ. (United Kingdom)
Ruikang K. Wang, Glasgow Univ. (United Kingdom)
Rupert C. D. Young, Glasgow Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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