Landsat-8 OLI Multispectral Image Dehazing Based on Optimized Atmospheric Scattering Model

Optical satellite images are often affected by haze atmospheric conditions, which degrades the quality of remote sensing (RS) data and reduces the accuracy of interpretation and classification. Hence, haze removal becomes a necessary preprocessing step for most of the applications of RS image. In th...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2021-12, Vol.59 (12), p.10255-10265
Main Authors: Guo, Jianhua, Yang, Jingyu, Yue, Huanjing, Hou, Chunping, Li, Kun
Format: Article
Language:English
Subjects:
Artificial satellites
Atmospheric conditions
Atmospheric modeling
Atmospheric scattering
Atmospheric scattering model
Atmospheric waves
Computational modeling
Earth
Haze
haze removal
haze transmission estimation
Landsat
Landsat satellites
Landsat-8 OLI multispectral image
Particle concentration
Remote sensing
Removal
Satellite imagery
Scattering
Spaceborne remote sensing
Visibility
Wavelength
wavelength and haze conditions dependence
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Summary:Optical satellite images are often affected by haze atmospheric conditions, which degrades the quality of remote sensing (RS) data and reduces the accuracy of interpretation and classification. Hence, haze removal becomes a necessary preprocessing step for most of the applications of RS image. In this article, we propose a novel haze removal method for Landsat-8 OLI multispectral image based on an optimized atmospheric scattering model. We focus on adaptively estimating the haze transmission map of each band by taking into account the effect of both wavelength and haze atmospheric conditions (haze particle size and haze particle concentration) thus improving dehazing performance. The experimental results on Landsat-8 OLI multispectral images show that the proposed dehazing model is able to remove haze successfully and significantly improve the image visibility as well as correct the spectral bias to some degree. Moreover, this method is simple and feasible, and has good practical value.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2020.3036972