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Article

Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images

1
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(21), 6053; https://doi.org/10.3390/s20216053
Received: 29 September 2020 / Revised: 21 October 2020 / Accepted: 22 October 2020 / Published: 24 October 2020
(This article belongs to the Special Issue Sensors and Deep Learning for Digital Image Processing)
Numerous applications are hindered by shadows in high resolution satellite remote sensing images, like image classification, target recognition and change detection. In order to improve remote sensing image utilization, significant importance appears for restoring surface feature information under shadow regions. Problems inevitably occur for current shadow compensation methods in processing high resolution multispectral satellite remote sensing images, such as color distortion of compensated shadow and interference of non-shadow. In this study, to further settle these problems, we analyzed the surface irradiance of both shadow and non-shadow areas based on a satellite sensor imaging mechanism and radiative transfer theory, and finally develop an irradiance restoration based (IRB) shadow compensation approach under the assumption that the shadow area owns the same irradiance to the nearby non-shadow area containing the same type features. To validate the performance of the proposed IRB approach for shadow compensation, we tested numerous images of WorldView-2 and WorldView-3 acquired at different sites and times. We particularly evaluated the shadow compensation performance of the proposed IRB approach by qualitative visual sense comparison and quantitative assessment with two WorldView-3 test images of Tripoli, Libya. The resulting images automatically produced by our IRB method deliver a good visual sense and relatively low relative root mean square error (rRMSE) values. Experimental results show that the proposed IRB shadow compensation approach can not only compensate information of surface features in shadow areas both effectively and automatically, but can also well preserve information of objects in non-shadow regions for high resolution multispectral satellite remote sensing images. View Full-Text
Keywords: irradiance restoration; shadow compensation; WorldView-3; multispectral satellite remote sensing image irradiance restoration; shadow compensation; WorldView-3; multispectral satellite remote sensing image
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MDPI and ACS Style

Han, H.; Han, C.; Huang, L.; Lan, T.; Xue, X. Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images. Sensors 2020, 20, 6053. https://doi.org/10.3390/s20216053

AMA Style

Han H, Han C, Huang L, Lan T, Xue X. Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images. Sensors. 2020; 20(21):6053. https://doi.org/10.3390/s20216053

Chicago/Turabian Style

Han, Hongyin, Chengshan Han, Liang Huang, Taiji Lan, and Xucheng Xue. 2020. "Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images" Sensors 20, no. 21: 6053. https://doi.org/10.3390/s20216053

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