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Adaptive Morphological Operation for High-Performance Weather Image Processing
http://hdl.handle.net/20.500.12678/0000006325
http://hdl.handle.net/20.500.12678/00000063257023021f-3beb-4674-893a-2774c078c25e
7188f0be-1f1f-4271-8d74-45bd5346094c
Name / File | License | Actions |
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Adaptive Morphological Operation for High-Performance Weather Image Processing.pdf (1.4 Mb)
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© 2018 ICAIT
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Publication type | ||||||
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Conference paper | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Adaptive Morphological Operation for High-Performance Weather Image Processing | |||||
Language | en | |||||
Publication date | 2018-11-02 | |||||
Authors | ||||||
Swe Swe Aung | ||||||
Itaru Nagayama | ||||||
Shiro Tamaki | ||||||
Description | ||||||
Morphological operations have been an integral part of enhancement of digital imaging programs, especially for filtering noise for improving the quality of image by utilizing the two most basic morphological operations, named as erosion and dilation, altogether. The main role of dilation is to fill the defined region in an image with pixels, while erosion removes pixels from the region. As we know, the method of erosion followed by dilation or dilation followed by erosion is indeed an attractive approach amongst researchers to deal with filtering noise problems. However, this approach needs more computation time and has a high percentage of losing essential pixel area. To cover these issues, this paper introduces a new approach called adaptive morphological operation to boost the performance of image enhancement. Based on 2011, 2013, 2015, and 2016 weather image datasets collected from WITH radar, which is installed on the rooftop of Information Engineering building, University of the Ryukyus, the experimental results confirm that the proposed approach is more efficient than the conventional approach. |
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Keywords | ||||||
Adaptive Morphological Operation, Dilation, Erosion | ||||||
Conference papers | ||||||
ICAIT-2018 | ||||||
1-2 November, 2018 | ||||||
2nd International Conference on Advanced Information Technologies | ||||||
Yangon, Myanmar | ||||||
Image Processing | ||||||
https://www.uit.edu.mm/icait-2018/ |