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The paper presents a data and task parallel low-level image processing environment for distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. At the application level we use task decomposition, based on the Image Application Task Graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus better speed-ups can be obtained. We validate our method on the multi-baseline stereo vision application
Published in:
Parallel Processing Workshops, 2001. International Conference on
Date of Conference: 2001
- Page(s):
- 39 - 44
- Meeting Date :
- 03 Sep 2001-07 Sep 2001
- ISSN :
- 1530-2016
- Print ISBN:
- 0-7695-1260-7
- INSPEC Accession Number:
- 7075337
- Conference Location :
- Valencia
- Digital Object Identifier :
- 10.1109/ICPPW.2001.951848
- Product Type:
- Conference Publications
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