Adaptive Morphological Operation for High-Performance Weather Image Processing

Swe Swe Aung; Itaru Nagayama; Shiro Tamaki

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Adaptive Morphological Operation for High-Performance Weather Image Processing

http://hdl.handle.net/20.500.12678/0000006325

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Adaptive Morphological Operation for High-Performance Weather Image Processing.pdf (1.4 Mb)	© 2018 ICAIT

Publication type
		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.
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/