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Remote Sens. 2016, 8(10), 844;

A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images

1,3,* and 1,3
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Author to whom correspondence should be addressed.
Academic Editors: Liming Zhou and Prasad S. Thenkabail
Received: 22 July 2016 / Revised: 22 September 2016 / Accepted: 11 October 2016 / Published: 14 October 2016
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Spatially varying haze is a common feature of most satellite images currently used for land cover classification and mapping and can significantly affect image quality. In this paper, we present a high-fidelity haze removal method based on Haze Optimized Transformation (HOT), comprising of three steps: semi-automatic HOT transform, HOT perfection and percentile based dark object subtraction (DOS). Since digital numbers (DNs) of band red and blue are highly correlated in clear sky, the R-squared criterion is utilized to search the relative clearest regions of the whole scene automatically. After HOT transform, spurious HOT responses are first masked out and filled by means of four-direction scan and dynamic interpolation, and then homomorphic filter is performed to compensate for loss of HOT of masked-out regions with large areas. To avoid patches and halo artifacts, a procedure called percentile DOS is implemented to eliminate the influence of haze. Scenes including various land cover types are selected to validate the proposed method, and a comparison analysis with HOT and Background Suppressed Haze Thickness Index (BSHTI) is performed. Three quality assessment indicators are selected to evaluate the haze removed effect on image quality from different perspective and band profiles are utilized to analyze the spectral consistency. Experiment results verify the effectiveness of the proposed method for haze removal and the superiority of it in preserving the natural color of object itself, enhancing local contrast, and maintaining structural information of original image. View Full-Text
Keywords: haze removal; HOT transform; BSHTI; homomorphic filter; percentile DOS haze removal; HOT transform; BSHTI; homomorphic filter; percentile DOS

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Jiang, H.; Lu, N.; Yao, L. A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images. Remote Sens. 2016, 8, 844.

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