Modular Algorithms for Multidimensional Signal Processing

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Four topics are being studied under the heading of modular algorithms for multidimensional signal processing. The first topic is an investigation of the subclass of rational transfer functions which can be represented in cascade lattice form. Second, a multichannel approach is made to the characterization of all orthogonal lattice configurations for two-dimensional (2-D) signals. A study of maximum entropy (ME) methods in relation to model constraints constitutes the third topic of study. This work is based on the investigators recent results regarding the optimality of recursive autoregressive models in terms minimizing a certain information theoretic distance from the ME solution. Finally, layer-pealing algorithms will be investigated for 2-D scattering arrays. This research concerns the extension of the lattice modeling approach to multidimensional signal processing. This lattice approach has been very influential in the case of one-dimensional signals such as audio because of its advantages for VLSI and also for adaptive processing. The researchers are working on the difficult problems of trying to extend these advantages to the two-dimensional case for application to video and computer vision.