Airborne Polarimetric Remote Sensing for Atmospheric Correction
Joint Authors
Liang, Tianquan
Sun, Xiaobing
Wang, Han
Ti, Rufang
Shu, Cunming
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-10
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The problem, whose targets can not be effectively identified for airborne remote sensing images, is mainly due to the atmospheric scattering effect.
This problem is necessary to be overcome.
According to the statistical evaluations method and the different characteristics of polarization between the objects radiance and atmospheric path radiation, a new atmospheric correction method for airborne remote sensing images was proposed.
Using this new method on the airborne remote sensing images which acquired on the north coast areas of China during the haze weather, we achieved a high quality corrected atmosphere-free image.
The results demonstrate the power of the method on the harbor area.
The results show that the algorithm, improving image contrast and image information entropy, can effectively identify the targets after atmospheric correction.
The image information entropy was enhanced from 5.59 to 6.62.
The research provides a new and effective atmospheric correction technical approach for the airborne remote sensing images.
American Psychological Association (APA)
Liang, Tianquan& Sun, Xiaobing& Wang, Han& Ti, Rufang& Shu, Cunming. 2015. Airborne Polarimetric Remote Sensing for Atmospheric Correction. Journal of Sensors،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1110425
Modern Language Association (MLA)
Liang, Tianquan…[et al.]. Airborne Polarimetric Remote Sensing for Atmospheric Correction. Journal of Sensors No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1110425
American Medical Association (AMA)
Liang, Tianquan& Sun, Xiaobing& Wang, Han& Ti, Rufang& Shu, Cunming. Airborne Polarimetric Remote Sensing for Atmospheric Correction. Journal of Sensors. 2015. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1110425
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110425