Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

Journal of Beijing University of Posts and Telecommunications ›› 2024, Vol. 47 ›› Issue (1): 106-111.

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ORB-SLAM Algorithm for Low Light Environment

LI Ping1, CAO Chaochao2   

  • Received:2022-11-14 Revised:2023-02-23 Online:2024-02-26 Published:2024-02-26
  • Contact: Ping Li E-mail:lipingjxau@163.com

Abstract: Aiming at the localization failure and tracking loss of visual simultaneous localization and map building (SLAM) in complex environments such as weak lighted or even totally dark, a vision SLAM algorithm suitable for weak light environment is proposed based on ORB-SLAM2, to which, a new adaptive image enhancement algorithm is applied. Image brightness is adapted by means of correction factor , which can be dynamically adjusted according to illuminance component of input image extracted by multi-scale Gaussian function. Performance of the algorithm is tested on public dataset. Simulation results show that the algorithm can efficiently help feature matching in complex environments such as weak lighted or even totally dark, consequently, the robustness of ORB-SLAM is improved effectually. 

Key words: low light environment, simultaneous localization and mapping, image enhancement, multi-scale Gaussian function, adaptive correction

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