PARALLEL ALGORITHMS FOR IMAGE-PROCESSING ON OMC

In this paper, we study a class of VLSI organizations with optical interconnects for fast solutions to several image processing tasks. The organization and operation of these architectures are based on a generic model called OMC, which is proposed to understand the computational limits in using free space optics in VLSI parallel processing systems. The relationships between OMC and shared memory models are discussed in this paper. Also, three physical implementations of OMC are presented. Using OMC, we present several parallel algorithms for fine grain image computing. We categorize our results in the following order. First, we present a set of processor efficient optimal O(log N) algorithms and a set of constant time algorithms for finding geometric properties of digitized images. Finally, we focus on special purpose designs tailored to meet both the computation and communication needs of problems such as those involving irregular sparse matrices.