Parallel image processing in heterogeneous computing network systems

We present a uniform construct of parallel programming for a set of image processing tasks based on our distributed computing primitive (DCP) concept. Our target architecture is a heterogeneous computing network system consisting of various high performance workstations connected through a local area network. We show that DCP has advantages over non-primitive PVM-based parallel approaches in three aspects: ease-of-use, automation, and optimization.