Block decomposition structures for the fast modular implementation of two-dimensional digital filters

Abstract

A general structure is presented for the block realization of two-dimensional infinite impulse response digital filters, which is based on the two-dimensional matrix convolution equations and the decomposition of their associated transfer function matrices. The proposed decomposition may be considered as an extension of the scalar decomposition technique, which has already been used for the realization of two-dimensional digital filters associated with two-variable polynomials. The decomposition structure is considered in two different forms, which correspond to the direct forms I and II. It is shown that if a given two-dimensional single-input, single-output filter is realizable, then realizable block decomposition structures may be always selected. The proposed approach is general and applies without any restriction for the block implementation of any two-dimensional filter. The resulting structures are characterized by high inherent parallelism, modularity, regularity, reconfigurability, local interconnections, and very high sampling and throughput rates. Thus they are well suited for VLSI implementation and implementation via multiprocessor systems and array processors, such as systolic and wavefront arrays.