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PLSMS model for restoration of the details concealed by light sources in nighttime hazed image

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Abstract

In the popular atmospheric scattering model applied to image dehazed, the scatter from the adjacent light sources on the camera sensor which has degraded the image quality is neglected, especially when some artificial light sources exist. Therefore, in the dehazing results, the light sources are always much brighter than those in the original image in order to enhance the majority details in the dark regions, which causes the details around the light sources to be obscured. We propose a novel image restoration model mainly based on point light source multiple scattering theory. An observed hazed image can be described as a linear combination of light being reflected from an imaged object itself and its multiple scattering component. The restoration quality of the artificial light sources and details around them may be improved by suppressing the multiple scattering which can be simulated by an APSF function. The key of our model is to find the appropriate APSF kernels by analysis and some experiments. Comparisons and evaluations of our restoration results with those from popular algorithms show that ours is better in details and colors recovery in dealing with light sources in nighttime hazed images.

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Acknowledgements

Thanks for Professor Yu Li, Jing Zhang and Yang Cao providing us their codes and synthesized image to test and comparison.

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Authors and Affiliations

  1. Tianjin Key Laboratory of Photoelectric Detection Technology and System, School of Artificial Intelligent, Tianjin Polytechnic University, Tianjin, 300387, China

    Chunming Tang

  2. School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, 300387, China

    Ruiyu Sun, Zheng Lian & Wenyan Zhu

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  1. Chunming Tang
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  2. Ruiyu Sun
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  4. Wenyan Zhu
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Correspondence to Chunming Tang.

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Tang, C., Sun, R., Lian, Z. et al. PLSMS model for restoration of the details concealed by light sources in nighttime hazed image. SIViP 15, 411–419 (2021). https://doi.org/10.1007/s11760-020-01761-w

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  • DOI: https://doi.org/10.1007/s11760-020-01761-w

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