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Fast and Scalable Selection Algorithms with Applications to Median Filtering
October 2003 (vol. 14 no. 10)
pp. 983-992

Abstract—The main contributions of this paper are in designing fast and scalable parallel algorithms for selection and median filtering. Based on the radix-\omega representation of data and the prune-and-search approach, we first design a fast and scalable selection algorithm on the arrays with reconfigurable optical buses (AROB). To the authors' knowledge, this is the most time efficient algorithm yet published, especially compared to the algorithms proposed by Han et al and Pan. Then, given an N x N image and a W x W window, based on the proposed selection algorithm, several scalable median filtering algorithms are developed on the AROB model with a various number of processors. In the sense of the product of time and the number of processors used, most of the proposed algorithms are time or cost optimal.

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Index Terms:
Median filer, scalable selection algorithm, parallel algorithm, image processing, reconfigurable optical bus system.
Citation:
Chin-Hsiung Wu, Shi-Jinn Horng, "Fast and Scalable Selection Algorithms with Applications to Median Filtering," IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 10, pp. 983-992, Oct. 2003, doi:10.1109/TPDS.2003.1239867
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