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|a 10.1109/TPAMI.2023.3341721
|2 doi
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|a eng
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| 100 |
1 |
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|a Ryu, Jiwoo
|e verfasserin
|4 aut
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| 245 |
1 |
2 |
|a A Fast Alpha-Tree Algorithm for Extreme Dynamic Range Pixel Dissimilarities
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|c 2024
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| 336 |
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|a Text
|b txt
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 03.04.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a The α-tree algorithm is a useful hierarchical representation technique which facilitates comprehension of images such as remote sensing and medical images. Most α-tree algorithms make use of priority queues to process image edges in a correct order, but because traditional priority queues are inefficient in α-tree algorithms using extreme-dynamic-range pixel dissimilarities, they run slower compared with other related algorithms such as component tree. In this paper, we propose a novel hierarchical heap priority queue algorithm that can process α-tree edges much more efficiently than other state-of-the-art priority queues. Experimental results using 48-bit Sentinel-2 A remotely sensed images and randomly generated images have shown that the proposed hierarchical heap priority queue improved the timings of the flooding α-tree algorithm by replacing the heap priority queue with the proposed queue: 1.68 times in 4-N and 2.41 times in 8-N on Sentinel-2 A images, and 2.56 times and 4.43 times on randomly generated images
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| 650 |
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|a Journal Article
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| 700 |
1 |
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|a Trager, Scott C
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wilkinson, Michael H F
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 46(2024), 5 vom: 01. Apr., Seite 3199-3212
|w (DE-627)NLM098212257
|x 1939-3539
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1 |
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|g volume:46
|g year:2024
|g number:5
|g day:01
|g month:04
|g pages:3199-3212
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|u http://dx.doi.org/10.1109/TPAMI.2023.3341721
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