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Intelligent Service Robotics
Erschienen in: Intelligent Service Robotics 4/2019

19.08.2019 | Original Research Paper

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

verfasst von: Shuhuan Wen, Xueheng Hu, Jinrong Ma, Fuchun Sun, Bin Fang

Erschienen in: Intelligent Service Robotics | Ausgabe 4/2019

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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.
Vorheriger Artikel Self-supervised damage-avoiding manipulation strategy optimization via mental simulation
Nächster Artikel Active object search in an unknown large-scale environment using commonsense knowledge and spatial relations

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Metadaten
Titel
Autonomous robot navigation using Retinex algorithm for multiscale image adaptability in low-light environment
verfasst von
Shuhuan Wen
Xueheng Hu
Jinrong Ma
Fuchun Sun
Bin Fang
Publikationsdatum
19.08.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Intelligent Service Robotics / Ausgabe 4/2019
Print ISSN: 1861-2776
Elektronische ISSN: 1861-2784
DOI
https://doi.org/10.1007/s11370-019-00287-6

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