A procedure for estimating the parameters associated with a linear phase signal is developed. When the data being modelled is composed of a linear phase signal corrupted by additive Gaussian noise the approach taken results in maximum-likelihood estimates of the linear phase parameters. These estimates are useful for detecting and estimating the presence of symmetry in both one and two dimensions. The effectiveness of the estimates is tested on both synthetic and real images.
['James A. Cadzow', 'Ramakrishna Kakarala']
Estimation of phase for noisy linear phase signals