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231223s2008 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2007.70836
|2 doi
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|a pubmed24n0605.xml
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|a DE-627
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|a eng
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| 100 |
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|a Wilkinson, Michael H F
|e verfasserin
|4 aut
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| 245 |
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|a Concurrent computation of attribute filters on shared memory parallel machines
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|c 2008
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 22.10.2008
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|a Date Revised 15.08.2008
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|a published: Print
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|a Citation Status MEDLINE
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|a Morphological attribute filters have not previously been parallelized, mainly because they are both global and non-separable. We propose a parallel algorithm that achieves efficient parallelism for a large class of attribute filters, including attribute openings, closings, thinnings and thickenings, based on Salembier's Max-Trees and Min-trees. The image or volume is first partitioned in multiple slices. We then compute the Max-trees of each slice using any sequential Max-Tree algorithm. Subsequently, the Max-trees of the slices can be merged to obtain the Max-tree of the image. A C-implementation yielded good speed-ups on both a 16-processor MIPS 14000 parallel machine, and a dual-core Opteron-based machine. It is shown that the speed-up of the parallel algorithm is a direct measure of the gain with respect to the sequential algorithm used. Furthermore, the concurrent algorithm shows a speed gain of up to 72 percent on a single-core processor, due to reduced cache thrashing
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|a Journal Article
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| 700 |
1 |
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|a Gao, Hui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hesselink, Wim H
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Jonker, Jan-Eppo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Meijster, Arnold
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 30(2008), 10 vom: 01. Okt., Seite 1800-13
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
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|g volume:30
|g year:2008
|g number:10
|g day:01
|g month:10
|g pages:1800-13
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| 856 |
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|u http://dx.doi.org/10.1109/TPAMI.2007.70836
|3 Volltext
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