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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 36, Iss. 35 — Dec. 10, 1997
  • pp: 9212–9224

Application of nonlinearity to wavelet-transformed images to improve correlation filter performance

Lamia S. Jamal-Aldin, Rupert C. D. Young, and Chris R. Chatwin  »View Author Affiliations


Applied Optics, Vol. 36, Issue 35, pp. 9212-9224 (1997)
http://dx.doi.org/10.1364/AO.36.009212


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Abstract

A useful filter for pattern recognition must strike a compromise between the conflicting requirements of in-class distortion tolerance and out-of-class discrimination. Such a filter will be bandpass in nature, the high-frequency response being attenuated to provide less sensitivity to in-class variations, while the low frequencies must be removed, since they compromise the discrimination ability of the filter. A convenient bandpass is the difference of Gaussian (DOG) function, which provides a close approximation to the Laplacian of Gaussian. We describe the effect of a preprocessing operation applied to a DOG filtered image. This operation is shown to result in greater tolerance to in-class variation while maintaining an excellent discrimination ability. Additionally, the introduction of nonlinearity is shown to provide greater robustness in the filter response to noise and background clutter in the input scene.

© 1997 Optical Society of America

History
Original Manuscript: April 28, 1997
Revised Manuscript: August 7, 1997
Published: December 10, 1997

Citation
Lamia S. Jamal-Aldin, Rupert C. D. Young, and Chris R. Chatwin, "Application of nonlinearity to wavelet-transformed images to improve correlation filter performance," Appl. Opt. 36, 9212-9224 (1997)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-36-35-9212


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