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231224s2011 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2011.183
|2 doi
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|a eng
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| 100 |
1 |
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|a Yuan, Hao
|e verfasserin
|4 aut
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| 245 |
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|a Running Max/Min Filters using 1+o(1) Comparisons per Sample
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|c 2011
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Revised 20.11.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a A running max (or min) filter asks for the maximum or (minimum) elements within a fixed-length sliding window. The previous best deterministic algorithm (developed by Gil and Kimmel, and refined by Coltuc) can compute the 1D max filter using 1.5+o(1) comparisons per sample in the worst case. The best known algorithm for independent and identically distributed input uses 1.25+o(1) expected comparisons per sample(by Gil and Kimmel). In this work, we show that the number of comparisons can be reduced to 1+o(1) comparisons per sample in the worst case. As a consequence of the new max/min filters, the opening (or closing) filter can also be computed using 1+o(1) comparisons per sample in the worst case, where the previous best work requires 1.5+o(1) comparisons per sample (by Gil and Kimmel); and computing the max and min filters simultaneously can be done in 2+o(1) comparisons per sample in the worst case, where the previous best work (by Lemire) requires 3 comparisons per sample. Our improvements over the previous work are asymptotic, that is, the number of comparisons is reduced only when the window size is large
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|a Journal Article
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1 |
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|a Atallah, Mikhail J
|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 33(2011), 12 vom: 30. Dez., Seite 2544-2548
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
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|g volume:33
|g year:2011
|g number:12
|g day:30
|g month:12
|g pages:2544-2548
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|u http://dx.doi.org/10.1109/TPAMI.2011.183
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|d 33
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|h 2544-2548
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