@article {15009,
	title = {Parallel algorithms for image histogramming and connected components with an experimental study (extended abstract)},
	journal = {ACM SIGPLAN Notices},
	volume = {30},
	year = {1995},
	month = {1995/08//},
	pages = {123 - 133},
	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.},
	keywords = {connected components, histogramming, IMAGE PROCESSING, image understanding, Parallel algorithms, scalable parallel processing},
	isbn = {0362-1340},
	doi = {10.1145/209937.209950},
	url = {http://doi.acm.org/10.1145/209937.209950},
	author = {Bader,David A. and JaJa, Joseph F.}
}
