High-speed architectures for digital image processing

This paper introduces the problem of and presents some state-of-the-art approaches for high-speed digital image processing. An architecture based on distributed arithmetic, which eliminates the use of multipliers, is described. A minimum-cycle-time filter architecture, which features a high degree of parallelism and pipelining, is shown to have a throughput rate that is independent of the filter order. Furthermore, a new multiprocessing-element architecture is proposed. This leads to a filter structure which can be implemented using identical building blocks. A modular VLSI architecture based on the decomposition of the kernel matrix of a two-dimensional (2-D) transfer function is also presented. In this approach, a general 2-D transfer function is expanded in terms of low-order 2-D polynomials. Each one of these 2-D polynomials is then implemented by a VLSI chip using a bit-sliced technique. In addition, a class of nonlinear 2-D filters based on the extension of one-dimensional (1-D) quadratic digital filters is introduced. It is shown that with the use of matrix decomposition, these 2-D quadratic filters can be implemented using linear filters with some extra operations. Finally, comparisons are made among the different approaches in terms of cycle time, latency, hardware complexity, and modularity.