Underwater image restoration via non-convex non-smooth variation and thermal exchange optimization

Qingliang Jiao; Ming Liu; Pengyu Li; Liquan Dong; Mei Hui; Lingqin Kong; Yuejin Zhao

doi:10.3390/jmse9060570

Underwater image restoration via non-convex non-smooth variation and thermal exchange optimization

Qingliang Jiao, Ming Liu^*, Pengyu Li, Liquan Dong, Mei Hui, Lingqin Kong, Yuejin Zhao

^*Corresponding author for this work

School of Optics and Photonics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.

Original language	English
Article number	570
Journal	Journal of Marine Science and Engineering
Volume	9
Issue number	6
DOIs	https://doi.org/10.3390/jmse9060570
Publication status	Published - Jun 2021

Keywords

Adapt parameter selection
Non-convex non-smooth variation
Thermal exchange optimization
Underwater DCP (dark channel prior)
Underwater image restoration

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10.3390/jmse9060570

Cite this

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title = "Underwater image restoration via non-convex non-smooth variation and thermal exchange optimization",

abstract = "The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.",

keywords = "Adapt parameter selection, Non-convex non-smooth variation, Thermal exchange optimization, Underwater DCP (dark channel prior), Underwater image restoration",

author = "Qingliang Jiao and Ming Liu and Pengyu Li and Liquan Dong and Mei Hui and Lingqin Kong and Yuejin Zhao",

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T1 - Underwater image restoration via non-convex non-smooth variation and thermal exchange optimization

AU - Jiao, Qingliang

AU - Liu, Ming

AU - Li, Pengyu

AU - Dong, Liquan

AU - Hui, Mei

AU - Kong, Lingqin

AU - Zhao, Yuejin

PY - 2021/6

Y1 - 2021/6

N2 - The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.

AB - The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.

KW - Adapt parameter selection

KW - Non-convex non-smooth variation

KW - Thermal exchange optimization

KW - Underwater DCP (dark channel prior)

KW - Underwater image restoration

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DO - 10.3390/jmse9060570

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JO - Journal of Marine Science and Engineering

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Underwater image restoration via non-convex non-smooth variation and thermal exchange optimization

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Keywords

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