Cellular computers for parallel region-level image processing

Abstract

It is well known that cellular computers can be used very effectively for parallel image processing at the pixel level, by assigning a processor to each level or block of pixels, and passing information as necessary between processors whose blocks are adjacent. This paper discusses the use of cellular computers for parallel processing of images at the region level, assigning a processor to each region and passing information between processors whose regions are related. The basic difference between the pixel and region levels is that the regions (e.g., obtained by segmenting the given image) and relationships differ from image to image, and even for a given image, they do not remain fixed during processing. Thus, one cannot use the standard type of cellular parallelism, in which the set of processors and interprocessor connections remain fixed, for processing at the region level. Reconfigurable cellular computers, in which the set of processors that each processor can communicate with can change during a computation, are more appropriate. A class of such computers is described, and general examples are given illustrating how such a computer could initially configure itself to represent a given decomposition of an image into regions, and dynamically reconfigure itself, in parallel, as regions merge or split.

The support of the U.S. Air Force Office of Scientific Research under Grant AFOSR-77-3271 is gratefully acknowledged, as is the help of Janet Salzman in preparing this paper. A slightly different version of this paper appears in Pattern Recognition 15, 1982, 41–60.