1. Adaptive Haze Removal for Single Remote Sensing Image
- Author
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Xiaoxi Pan, Zhiguo Jiang, Jiajie Chen, and Fengying Xie
- Subjects
Haze ,General Computer Science ,Computer science ,haze removal ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,0211 other engineering and technologies ,General Engineering ,02 engineering and technology ,Atmospheric model ,Real image ,GeneralLiterature_MISCELLANEOUS ,dark channel-saturation prior ,remote sensing ,Adaptive dehazing ,Histogram ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,General Materials Science ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,lcsh:TK1-9971 ,ComputingMethodologies_COMPUTERGRAPHICS ,021101 geological & geomatics engineering ,Remote sensing - Abstract
Haze is a common phenomenon in remote sensing images, which limits their applications. In this paper, a novel adaptive dehazing method is proposed for remote sensing images. First, a new prior, namely, dark channel-saturation prior, is developed based on the relation between dark channel and saturation of haze-free remote sensing images. Second, optimal transmission is estimated through the proposed prior on the basis of haze imaging model. Finally, using the estimated transmission, haze is removed from the images through the haze imaging model. Because no parameter needs to be set manually in this proposed method, the nonuniform haze can be adaptively removed. Experiments are carried out on simulated images and real images respectively. Compared with the other state-of-the-art methods, the proposed method can recover the scene in hazy regions more clearly along with better information retainability in haze-free regions.
- Published
- 2018
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