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Many image processing algorithms have a very high execution time if only a processor is used for processing them. Using a SIMD parallel structure for its execution could reduce this time. This is particularly important in the case of algorithms that must be processed in real time. The use of networks of PC is an appealing solution that besides its low cost, takes advantage from both the high speed of actual interconnection networks, and the high-performance of PC. In this paper we present a model that explicitly considers system parameters, network parameters, and application parameters. So, the speed and communication model of the considered network, the workstations and PC computing power, the per-pixel computational cost of the algorithms (that can be constant or variable), and a variable number of computers have been considered. We do not aim to evaluate the processing of high and medium-level algorithms of a MISD structure, but we present the first results of our evaluations for iterative low-level image processing applications. Specifically, we give a prediction model to distribute the data to each processor of a distributed system, minimizing the processors' idle time.