A Fast Alpha-Tree Algorithm for Extreme Dynamic Range Pixel Dissimilarities
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 ineffi...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 5 vom: 12. Mai, Seite 3199-3212 |
|---|---|
| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2024
|
| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article |
| Résumé: | 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 |
|---|---|
| Description: | Date Revised 03.04.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1939-3539 |
| DOI: | 10.1109/TPAMI.2023.3341721 |