We present a high-SNR approach to estimating the orientation of distor
ted target objects, where the distortion is out-of-plane rotation. The
presence and position of the targets are detected with a bank of dist
ortion-invariant correlation filters. The filter set we use, known as
hybrid composite filters, yields complex responses at the target locat
ions, The peak magnitude responses indicate target locations. The corr
elation phase angles, at the target locations, are linearly combined i
nto complex signatures unique to a particular orientation. A maximum-l
ikelihood M-ary classification algorithm is used to determine the most
likely orientation from a finite number of orientations. In practice,
we do not use all the hybrid filters and the ones we do use are optim
ally selected and combined for detection and discrimination. Given the
target location, additional filtering can be accomplished with an inn
er-product operation rather than correlation. A second set of filters,
optimized for angle estimation, are applied as inner products at the
target locations to construct the orientation signatures. A rigorous m
athematical treatment of the optimum signature detection architecture
is presented and numerical simulations demonstrate the capabilities of
this approach. (C) 1997 Society of Photo-Optical Instrumentation Engi
neers.