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Parallel algorithms for image histogramming and connected components with an experimental study

delete1996-06-01
delete16
PRE
AI
D
David A. Bader *
J
Joseph F. JáJá
DOI：10.1006/jpdc.1996.0079delete
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Abstract

Abstract

En 中文
This paper presents efficient and portable implementations of two useful primitives in image processing algorithms, histogramming and connected components. Our general framework is a single-address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. Our connected components algorithm uses a novel approach for parallel merging which performs drastically limited updating during iterative steps, and concludes with a total consistency update at the final step. The algorithms have been coded in SPLIT-C and run on a variety of platforms. Our experimental results are consistent with the theoretical analysis and provide the best known execution times for these two primitives, even when compared with machine-specific implementations. (C) 1996 Academic Press, Inc.
Keywords:
COMPUTERS
EFFICIENT

Journal

Journal of Parallel and Distributed Computing cover
Journal of Parallel and Distributed Computing
IF:
4
Papers:
3.8K
Citations:
4.8K

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No organization information available