Robust polarization-based underwater image enhancement method using anchor brightness adaptation
•In previous studies, when estimating the DoP of background light, relying only on the AoP of the only pixel is vulnerable to interference from camera random noise. To solve this problem, we propose an effective neighborhood high fidelity constraint (NHFC) that can estimate the DoP of the background...
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| Veröffentlicht in: | Optics and lasers in engineering Jg. 169; S. 107737 |
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| Abstract | •In previous studies, when estimating the DoP of background light, relying only on the AoP of the only pixel is vulnerable to interference from camera random noise. To solve this problem, we propose an effective neighborhood high fidelity constraint (NHFC) that can estimate the DoP of the background light more accurately and robustly.•method will be proposed to estimate the intensity of the background light at infinity using the limit idea, which provides an accurate and fast estimation of the most suitable background light area.•An anchor brightness adaptation algorithm will be proposed to eliminate the side effect of inaccurate exposure of the enhanced image, the process is effective and requires no interaction.•The experiments were conducted in total darkness to simulate the underwater nighttime optical imaging environment.
Most of the polarization-based image enhancement methods do not take into account the inaccurate parameter estimation caused by the amplified camera noise at low illumination conditions. To solve this problem, this paper proposes a robust polarization-based underwater image enhancement method using anchor brightness adaptation (ABA). Relying on the relationship between the Stokes Vector and the angle of polarization (AoP), the proposed neighborhood high fidelity constraint (NHFC) can robustly select the region of the background light that is most suitable for parameter estimation, greatly reducing the interference of camera random noise under low illumination conditions and making full use of the characteristics of polarized optical imaging. The background light intensity at infinity and the scene transmission map are then estimated based on the polarization characteristics of the scene, thus effectively enhancing the image. Finally, ABA is introduced with the help of greyscale information of the original image to ensure the best exposure of the enhanced image. The experiments simulate underwater imaging at night, and the results show that the enhancement performance of this method is stable and can effectively solve the problem of being susceptible to random noise interference at low light, which has better applicability for real-time underwater image enhancement. |
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| AbstractList | •In previous studies, when estimating the DoP of background light, relying only on the AoP of the only pixel is vulnerable to interference from camera random noise. To solve this problem, we propose an effective neighborhood high fidelity constraint (NHFC) that can estimate the DoP of the background light more accurately and robustly.•method will be proposed to estimate the intensity of the background light at infinity using the limit idea, which provides an accurate and fast estimation of the most suitable background light area.•An anchor brightness adaptation algorithm will be proposed to eliminate the side effect of inaccurate exposure of the enhanced image, the process is effective and requires no interaction.•The experiments were conducted in total darkness to simulate the underwater nighttime optical imaging environment.
Most of the polarization-based image enhancement methods do not take into account the inaccurate parameter estimation caused by the amplified camera noise at low illumination conditions. To solve this problem, this paper proposes a robust polarization-based underwater image enhancement method using anchor brightness adaptation (ABA). Relying on the relationship between the Stokes Vector and the angle of polarization (AoP), the proposed neighborhood high fidelity constraint (NHFC) can robustly select the region of the background light that is most suitable for parameter estimation, greatly reducing the interference of camera random noise under low illumination conditions and making full use of the characteristics of polarized optical imaging. The background light intensity at infinity and the scene transmission map are then estimated based on the polarization characteristics of the scene, thus effectively enhancing the image. Finally, ABA is introduced with the help of greyscale information of the original image to ensure the best exposure of the enhanced image. The experiments simulate underwater imaging at night, and the results show that the enhancement performance of this method is stable and can effectively solve the problem of being susceptible to random noise interference at low light, which has better applicability for real-time underwater image enhancement. |
| ArticleNumber | 107737 |
| Author | Mi, Zetian Wang, Yujia Li, Yafeng Wang, Yulin Chen, Yuehan Fu, Xianping |
| Author_xml | – sequence: 1 givenname: Yuehan surname: Chen fullname: Chen, Yuehan organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China – sequence: 2 givenname: Yafeng surname: Li fullname: Li, Yafeng organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China – sequence: 3 givenname: Yulin surname: Wang fullname: Wang, Yulin organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China – sequence: 4 givenname: Zetian surname: Mi fullname: Mi, Zetian organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China – sequence: 5 givenname: Yujia surname: Wang fullname: Wang, Yujia organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China – sequence: 6 givenname: Xianping surname: Fu fullname: Fu, Xianping email: fxp@dlmu.edu.cn organization: Information Science and Technology School, Dalian Maritime University, Dalian 116026, China |
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| Cites_doi | 10.1109/TIP.2017.2663846 10.1364/OE.433072 10.1109/TIP.2018.2813092 10.1109/TPAMI.2008.85 10.1109/JPHOT.2018.2791517 10.1016/j.optcom.2018.12.022 10.1016/j.optlaseng.2021.106785 10.1016/j.optlaseng.2023.107550 10.1109/TIP.2015.2491020 10.1109/18.119732 10.1109/JOE.2015.2469915 10.1007/s10489-022-03767-y 10.1364/OE.434398 10.1016/S1076-5670(04)30002-9 10.1016/B978-0-12-336156-1.50061-6 10.1109/TSMC.2017.2788902 10.1109/TIP.2019.2955241 10.1109/ACCESS.2019.2932130 10.1364/OE.24.009826 |
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| Snippet | •In previous studies, when estimating the DoP of background light, relying only on the AoP of the only pixel is vulnerable to interference from camera random... |
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| SubjectTerms | Adaptive brightness algorithm Neighborhood constraint algorithm Polarization imaging Underwater image enhancement |
| Title | Robust polarization-based underwater image enhancement method using anchor brightness adaptation |
| URI | https://dx.doi.org/10.1016/j.optlaseng.2023.107737 |
| Volume | 169 |
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