Abstract
This paper considers how the image restoration technique of Geman and Geman, which involves searching for the maximum a posteriori distribution of an image modelled as bounded Markov random fields using simulated annealing, can be approximated on a parallel SIMD processor array, the ICL Distributed Array Processor (DAP). For the version implemented, the potential speed-up over an equivalent serial processor is equal to half the number of processors in the array, or 2048 for the 64×64 DAP. The time taken by the DAP for one updating cycle is about 30 ms, and the typical complete picture restoration consisting of 1000 annealing cycles takes around 30 s. A method of increasing the efficiency of the present algorithm is suggested and the possibility of making the algorithm work with several frames of data collected over time is discussed.
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