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Autonomous robot navigation using Retinex algorithm for multiscale image adaptability in low-light environment

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Abstract

This paper proposes an improved Retinex theory based on a weighted guided filter method to enhance images in low-light conditions. The captured images under low illumination can cause dimness, distortion or details loss. We use the weighted guided filter method to perform illumination estimation and the original image is regarded as the guidance image, which can avoid color distortion and over-enhancement. It can adjust the regularization parameter adaptively based on the image content. Perceptual contrast is improved by using an illumination enhancement method with dynamic adjustment. To test the validness of our algorithm, the weighted guided filter method proposed in this paper is compared with bilateral filter and the guided filter method. Finally, experiment under low illumination is implemented on a NAO robot by using the proposed weighted guided filter method based on EKF-SLAM. The experiment result demonstrates that the proposed weighted guided filter method is feasible and effective in low-light environment.

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Acknowledgements

The work was partly supported by the National Natural Science Foundation of China (Project Nos. 61773333, 61503212), Projects of International Cooperation and Exchanges NSFC (61621136008), the Major Project of Science and Technology in Hebei Universities (Project No. ZD2016150).

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Authors and Affiliations

  1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China

    Shuhuan Wen, Xueheng Hu & Jinrong Ma

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Fuchun Sun & Bin Fang

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  1. Shuhuan Wen
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  2. Xueheng Hu
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  3. Jinrong Ma
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  4. Fuchun Sun
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  5. Bin Fang
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Correspondence to Shuhuan Wen.

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Wen, S., Hu, X., Ma, J. et al. Autonomous robot navigation using Retinex algorithm for multiscale image adaptability in low-light environment. Intel Serv Robotics 12, 359–369 (2019). https://doi.org/10.1007/s11370-019-00287-6

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  • DOI: https://doi.org/10.1007/s11370-019-00287-6

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