Parallel algorithms for image histogramming and connected components with an experimental study (extended abstract)

TitleParallel algorithms for image histogramming and connected components with an experimental study (extended abstract)
Publication TypeJournal Articles
Year of Publication1995
AuthorsBader DA, JaJa JF
JournalACM SIGPLAN Notices
Volume30
Issue8
Pagination123 - 133
Date Published1995/08//
ISBN Number0362-1340
Keywordsconnected components, histogramming, IMAGE PROCESSING, image understanding, Parallel algorithms, scalable parallel processing
Abstract

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. More efficient implementations of Split-C will likely result in even faster execution times.

URLhttp://doi.acm.org/10.1145/209937.209950
DOI10.1145/209937.209950