Improving the false alarm capabilities of the maximum average correlation height correlation filter

We show that the maximum average correlation height (MACH) correlation filter overemphasizes the importance of the average training image leading to poor discrimination of the desired class images from clutter images. To overcome this, two new metrics termed the all image correlation height (AICH) and the modified average similarity measure (MASM) are introduced and optimized in a new correlation de- sign. The resulting filter exhibits improved clutter rejection performance while retaining the attractive distortion tolerance feature of the MACH filter. Simulation results based on a simulated synthetic aperture radar (SAR) image database are presented to illustrate the new filter's proper- ties.