Modular architectures for two-dimensional digital signal processing

The implementation of highly modular two-dimensional (2-D) digital filters is addressed. The idea of matrix decomposition is used to provide increased parallelism and regularity. Four different structures, namely, the transversal, the distributed arithmetic, the stored product, and the systolic array, are considered. For comparison purposes, the direct implementation is included. An analysis of each of each is performed and comparisons are made in terms of hardware cost, cycle time, finite register length effects, and regularity. It is found that the systolic array structure seems to offer the best compromise among the various conflicting figures of merit. The distributed arithmetic structure is shown to be superior in the case of low-order filters, while the stored product structure is preferable for high-order filters. The inherent parallelism and high throughput rate of these structures make them suitable for real-time image processing applications