Composite filter design for minimal correlation peak shape variation in cluttered images

Joergen Karlholm

doi:10.1117/12.381589

31 March 2000 Composite filter design for minimal correlation peak shape variation in cluttered images

Joergen Karlholm

Proceedings Volume 4043, Optical Pattern Recognition XI; (2000) https://doi.org/10.1117/12.381589
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In several recent articles it has been suggested that the shape of the correlation peak be used to distinguish between target and clutter. The peak shape is characterized in terms of some features, such as geometrical moments, which are then fed into a classifier that decides whether the peak was generated by target or clutter. The classification can be facilitated by an appropriate filter design. The maximum average correlation height (MACH) filter was designed to product similar correlation planes for target variations present in the training set. In this article we present generalizations of the MACH filter with the intention of decreasing the peak shape variation for targets in severe clutter. We show that by taking into account the non- overlapping character of the background noise and focusing the MACH correlation plane similarity requirement to the peak neighborhood, it is possible to simultaneously achieve a small variation in correlation peak shape and high peak- to-sidelobe ratios for cluttered images.

Citation Download Citation

Joergen Karlholm "Composite filter design for minimal correlation peak shape variation in cluttered images", Proc. SPIE 4043, Optical Pattern Recognition XI, (31 March 2000); https://doi.org/10.1117/12.381589

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