Abstract
We investigate composite Fourier-plane nonlinear filters for distortion-invariant pattern recognition. Different types of noise such as spatially nonoverlapping color background noise, other nontarget objects, real scene noise, and additive white noise are used to investigate the performance of the filter. Computer simulation results are presented to show the performance enhancement using Fourier-plane nonlinearities in the composite filter designs. The training image sets and the test image sets are generated by in-plane and out-plane rotation of different aircraft.
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