Analysis of a model for parallel image processing

Abstract

An increasing awareness of the need for high speed parallel processing systems for image analysis has stimulated a great deal of interest in the design and development of such systems. Efficient processing schemes for several specific problems have been developed providing some insight into the general problems encountered in designing efficient image processing algorithms for parallel architectures. However it is still not clear what architecture or architectures are best suited for image processing in general, or how one may go about determining those which are. An approach that would allow application requirements to specify architectural features would be useful in this context. Working towards this goal, general principles are outlined for formulating parallel image processing tasks by exploiting parallelism in the algorithms and data structures employed. A synchronous parallel processing model is proposed which governs the communication and interaction between these tasks. This model presents a uniform framework for comparing and contrasting different formulation strategies. In addition, techniques are developed for analyzing instances of this model to determine a high level specification of a parallel architecture that best ‘matches’ the requirements of the corresponding application. It is also possible to derive initial estimates of the component capabilities that are required to achieve predefined performance levels. Such analysis tools are useful both in the design stage, in the selection of a specific parallel architecture, or in efficiently utilizing an existing one. In addition, the architecture independent specification of application requirements makes it a useful tool for benchmarking applications.