2024-03-29T08:45:59Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/6325
2022-03-24T23:17:08Z
1582963342780:1605779935331
user-uit
Adaptive Morphological Operation for High-Performance Weather Image Processing
Swe Swe Aung
Itaru Nagayama
Shiro Tamaki
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.
2018-11-02
http://hdl.handle.net/20.500.12678/0000006325
https://meral.edu.mm/records/6325