Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 57, Issue 11, Pages 9124-9137Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2019.2924940
Keywords
Remote sensing; Sensors; Correlation; Cloud computing; Estimation; Clouds; Earth; Elliptical boundary; haze thickness prior; visible remote sensing image dehazing
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Funding
- National Key Research and Development Program [2016YFC0801003]
- National Natural Science Foundation of China [61772058]
- Fundamental Research Funds for the Central Universities
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Remote sensing images play important roles in various earth surface observation applications. However, the hazy state of surface atmosphere can visually decrease the contrast and availability of remote sensing images. In this paper, we propose a haze and thin cloud removal method for single visible remote sensing images, which aims to robustly estimate haze thickness, atmospheric light, and transmission value from a remote sensing image with dense haze or thin cloud, and finally recovers a haze-free image. An elliptical boundary prior (EBP) is proposed to transform the haze thickness in each local patch from the pixels cluster in the spectral space, which is surrounded by an ellipse. With the aim of preventing highlight objects influences, an atmospheric light estimation approach is presented. The correlation of transmission and haze thickness is reconstructed to develop the scattering model for remote sensing images. The experimental results demonstrate that the proposed method can not only significantly improve the contrast and restore textures of various kinds of hazy remote sensing images but also well preserve the spectral information of visible bands.
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