A New Robust Method for Two-Dimensional Inverse Filtering

In this paper, we present a novel method for inverse filtering a two dimensional (2-D) signal using phase-based processing techniques. A 2-D sequence can be represented by a sufficient number of samples of the phase of its Fourier transform and its region of support. This is exploited to perform deconvolution. We examine the effects of additive noise and incomplete knowledge of the point spread function on the performance of this deconvolution method and compare it with other 2-D deconvolution methods. The problem of finding the region of support will also be briefly addressed. Finally, an application example will be presented.