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Underwater image enhancement using an edge-preserving filtering Retinex algorithm

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A Correction to this article was published on 11 April 2020

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Abstract

We develop a novel edge-preserving filtering retinex algorithm for single underwater image enhancement, in which gradient domain guided image filtering (GGF) priors of reflection and illumination are embedded into a retinex-based variational framework for promoting image structures and reducing artifacts or noise. We transform an underwater image enhancement issue into a two-phase objective function. We first employ a general retinex-based method to generate guidance reflection and illumination, and then we use GGF to fuse fine structures of guidance reflection and illumination into ideal reflection and illumination. Meanwhile, the l2 norm is efficiently imposed on GGF priors which measure gradient errors between latent and ideal estimations of reflection and illumination. Then we derive an efficient optimization scheme to address the proposed model, which is fast implemented on pixel-wise operations and requires no prior knowledge about imaging conditions. Final experiments demonstrate the effectiveness of the proposed method in structures promotion, artifacts or noise suppression, naturalness and color preservation. Compared with several leading methods, the proposed method yields better subjective results and objective assessments. Furthermore, the utility of our method is extended for enhancing sandstorm and low illumination images.

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  • 11 April 2020

    In the original publication, Equations were incorrectly presented. The original article has been corrected.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments. The authors also would like to thank Chongyi Li, Miao Yang, Arcot Sowmya, Karen Panetta and Chen Gao for providing their available source codes and related materials. This work was supported in part by the National Natural Science Foundation of China under Grant 61701245, in part by The Startup Foundation for Introducing Talent of NUIST 2243141701030, in part by A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Jiangsu Technology and Engineering Center of Meteorological Sensor Network, School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Peixian Zhuang

  2. Fujian Key Laboratory of Sensing and Computing for Smart City, School of Information Science and Engineering, Xiamen University, Xiamen, 361005, China

    Xinghao Ding

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  1. Peixian Zhuang
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Correspondence to Peixian Zhuang.

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The original version of this article was revised: Equations were incorrectly presented.

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Zhuang, P., Ding, X. Underwater image enhancement using an edge-preserving filtering Retinex algorithm. Multimed Tools Appl 79, 17257–17277 (2020). https://doi.org/10.1007/s11042-019-08404-4

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  • DOI: https://doi.org/10.1007/s11042-019-08404-4

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