Top down structured parallelisation of embedded image processing applications

Abstract

The authors present a general system design method which is intended to support parallelisation of complete image processing applications using MIMD processors. The approach is based upon the utilisation of a generic system level parallel processor architecture, the 'pipeline processor farm'(PPF), and is applicable to any embedded application with continuous input/output. The design method is illustrated using applications from the fields of computer vision and image coding. The design model accommodates several commonly exploited parallel processing paradigms, maps conveniently to the software structure of most image processing algorithms, provides incrementally scalable performance, and enables upper-bound speedups to be easily estimated from profiling data generated by the original sequential implementation of the application. It is believed that the approach has significant application in parallel embedded systems design, in the development environment, and in simulation work for computationally intensive image coding algorithms.