In-place SIMD Accelerated Mathematical Morphology
Pages 76 - 79
Abstract
This paper describes an in-place SIMD accelerated method of mathematical morphology grayscale operators' erosion and dilation. These two operators can be used as building blocks to form a whole suite of additional operators, such as opening, closing, ultimate erosion and ultimate dilation. The described method is compared with OpenCV library as a baseline, and with itself, using different register sizes and data types.
References
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Li, Yong, Huayi Wu, Hanwei Xu, Ru An, Jia Xu, and Qisheng He. "A gradient-constrained morphological filtering algorithm for airborne LiDAR." Optics & Laser Technology 54 (2013): 288--296.
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Mongus, Domen, and Borut Žalik. "Parameter-free ground filtering of LiDAR data for automatic DTM generation." ISPRS Journal of Photogrammetry and Remote Sensing 67 (2012): 1--12.
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Li, Yong, Bin Yong, Huayi Wu, Ru An, Hanwei Xu, Jia Xu, and Qisheng He. "Filtering airborne lidar data by modified white top-hat transform with directional edge constraints." Photogrammetric Engineering & Remote Sensing 80, no. 2 (2014): 133--141.
[4]
Soille, P. "Morphological Image Analysis: Principles and Applications." (1999): 89--125.
[5]
Estérie, Pierre, Joel Falcou, Mathias Gaunard, and Jean-Thierry Lapresté. "Boost. simd: generic programming for portable simdization." In Proceedings of the 2014 Workshop on Programming models for SIMD/Vector processing, pp. 1--8. ACM, 2014.
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Index Terms
- In-place SIMD Accelerated Mathematical Morphology
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Published In
March 2018
146 pages
ISBN:9781450363587
DOI:10.1145/3206157
Copyright © 2018 ACM.
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In-Cooperation
- University of Florida: University of Florida
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 09 March 2018
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- Research-article
- Research
- Refereed limited
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- Javna agencija za raziskovalno dejavnost Republike Slovenije
Conference
ICBDE '18
ICBDE '18: 2018 International Conference on Big Data and Education
March 9 - 11, 2018
HI, Honolulu, USA
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