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Denoising Real-World Low Light Surveillance Videos Based on Trilateral Filter

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Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology (IoTCIT 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1197))

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Abstract

In this paper, a real-world denoising method for surveillance videos based on the trilateral filter is proposed. The algorithm is faced with challenges, including the absence of “ground truth” images and the complexity of the spatio-temporal distribution of the noise signal. However, experimental results have demonstrated that noise on stationary objects in such situations can be easily eliminated by averaging neighboring frames. Consequently, effective noise removal throughout the entire video can be achieved by accurately tracking and filtering moving objects along their trajectories. The model can be broadly divided into four steps. Firstly, coarse motion vectors are obtained through bilateral motion estimation. Secondly, the error vectors are judged and corrected using an amplitude-phase filter. Thirdly, these vectors are refined by performing a full searching in a small area. Finally, the noise is removed by applying a trilateral filter along the trajectory. The effectiveness of our model has been confirmed through numerous experiments, showcasing superior performance in both visualization and quantitative testing.

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Acknowledgement

This work is partly supported by the NSFC under No. 52204177 and No. 52304182.

Author information

Authors and Affiliations

  1. Guojia Wan Coal Mine Branch, Guoneng Yulin Energy Co., Ltd., Yulin, China

    Peng Xu, Xiong Zhang & Yan Shang

  2. Department of Information and Control, China University of Mining and Technology, Xuzhou, China

    Ping Zheng, Lijuan Zheng, Haoxiang Zhang & He Jiang

  3. Department of Computer Science, China University of Mining and Technology, Xuzhou, China

    Yiming Geng & Jiacong Gao

Authors
  1. Peng Xu
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  2. Ping Zheng
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  3. Lijuan Zheng
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  4. Xiong Zhang
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  5. Yan Shang
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  6. Haoxiang Zhang
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  7. Yiming Geng
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  8. Jiacong Gao
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  9. He Jiang
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Corresponding author

Correspondence to He Jiang .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, Hunan, China

    Jian Dong

  2. School of Information Engineering, Shenzhen University, Shenzhen, Guangdong, China

    Long Zhang

  3. School of Information and Control Engineering, China University of Mining and Technolog, Xuzhou, Jiangsu, China

    Deqiang Cheng

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Xu, P. et al. (2024). Denoising Real-World Low Light Surveillance Videos Based on Trilateral Filter. In: Dong, J., Zhang, L., Cheng, D. (eds) Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology. IoTCIT 2023. Lecture Notes in Electrical Engineering, vol 1197. Springer, Singapore. https://doi.org/10.1007/978-981-97-2757-5_64

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  • DOI: https://doi.org/10.1007/978-981-97-2757-5_64

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2756-8

  • Online ISBN: 978-981-97-2757-5

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