Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Research on the edge extraction algorithm for pollution clouds based on wavelet transform

Authors
Shunhua Liu, Jin Gu, Xun Sun, Zhizhen Zhu
Corresponding Author
Shunhua Liu
Available Online December 2016.
DOI
https://doi.org/10.2991/iceeecs-16.2016.173How to use a DOI?
Keywords
Pollution Clouds; Monitoring; Edge; Wavelet Transform
Abstract
According to the high requirement for time efficiency of monitoring on pollution clouds, based on the modern infrared telemetry technology and spectral imaging technology, the edge extraction algorithm for pollution clouds is established by using the wavelet transform principle, and the damage range of pollution clouds can be calculated quickly after proper expansion and the superposition with original images. In this paper, this algorithm is verified scientific and has a good processing effect by simulating smoke screen instead of pollution clouds, which can provide effective means for the real-time and accurate monitoring of pollution clouds.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Part of series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
https://doi.org/10.2991/iceeecs-16.2016.173How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shunhua Liu
AU  - Jin Gu
AU  - Xun Sun
AU  - Zhizhen Zhu
PY  - 2016/12
DA  - 2016/12
TI  - Research on the edge extraction algorithm for pollution clouds based on wavelet transform
BT  - 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.173
DO  - https://doi.org/10.2991/iceeecs-16.2016.173
ID  - Liu2016/12
ER  -