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3 April 2024 CADCP: a method for chromatic haze compensation on remotely sensed images
D. S. Sidorchuk, M. A. Pavlova, D. O. Kushchev, M. A. Selyugin, I. P. Nikolaev, D. A. Bocharov
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Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 1307216 (2024) https://doi.org/10.1117/12.3023507
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia
Abstract
Remote sensing images often suffer from different types of haze. Its presence significantly complicates remotely sensed image analysis that is crucial for monitoring of land state and precision agriculture. Currently existing remote sensing dehazing methods are designed for achromatic haze, but in cases such as smoke from fires or sandstorms, the haze may have its own pronounced coloration. In this paper we propose a new hazed image formation model that considers chromatic haze. Using this model we propose a new single image dehazing method CADCP that is based on color attenuation and dark channel priors. For quality assessment of the proposed method we generated a dataset of remotely sensed images with simulated chromatic haze. The generated dataset includes data with various haze spatial distribution and density. Quality evaluation results including qualitative and quantitative approaches demonstrated better results of the proposed method comparing with other existing methods.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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D. S. Sidorchuk, M. A. Pavlova, D. O. Kushchev, M. A. Selyugin, I. P. Nikolaev, and D. A. Bocharov "CADCP: a method for chromatic haze compensation on remotely sensed images", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 1307216 (3 April 2024); https://doi.org/10.1117/12.3023507
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KEYWORDS
Air contamination
Remote sensing
Signal attenuation
Image acquisition
Image processing
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