Evaluation of Image Enhancement Techniques for Vision-Based Navigation under Low Illumination
Joint Authors
Rawashdeh, Samir A.
Aladem, Mohamed
Baek, Stanley
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-20
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Cameras are valuable sensors for robotics perception tasks.
Among these perception tasks are motion estimation, localization, and object detection.
Cameras are attractive sensors because they are passive and relatively cheap and can provide rich information.
However, being passive sensors, they rely on external illumination from the environment which means that their performance degrades in low-light conditions.
In this paper, we present and investigate four methods to enhance images under challenging night conditions.
The findings are relevant to a wide range of feature-based vision systems, such as tracking for augmented reality, image registration, localization, and mapping, as well as deep learning-based object detectors.
As autonomous mobile robots are expected to operate under low-illumination conditions at night, evaluation is based on state-of-the-art systems for motion estimation, localization, and object detection.
American Psychological Association (APA)
Aladem, Mohamed& Baek, Stanley& Rawashdeh, Samir A.. 2019. Evaluation of Image Enhancement Techniques for Vision-Based Navigation under Low Illumination. Journal of Robotics،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1186963
Modern Language Association (MLA)
Aladem, Mohamed…[et al.]. Evaluation of Image Enhancement Techniques for Vision-Based Navigation under Low Illumination. Journal of Robotics No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1186963
American Medical Association (AMA)
Aladem, Mohamed& Baek, Stanley& Rawashdeh, Samir A.. Evaluation of Image Enhancement Techniques for Vision-Based Navigation under Low Illumination. Journal of Robotics. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1186963
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186963