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http://dx.doi.org/10.12652/Ksce.2022.42.5.0741

Experiment on Low Light Image Enhancement and Feature Extraction Methods for Rover Exploration in Lunar Permanently Shadowed Region  

Park, Jae-Min (Korea Institute of Civil Engineering and Building Technology)
Hong, Sungchul (Inha University)
Shin, Hyu-Soung (Korea Institute of Civil Engineering and Building Technology)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.42, no.5, 2022 , pp. 741-749 More about this Journal
Abstract
Major space agencies are planning for the rover-based lunar exploration since water-ice was detected in permanently shadowed regions (PSR). Although sunlight does not directly reach the PSRs, it is expected that reflected sunlight sustains a certain level of low-light environment. In this research, the indoor testbed was made to simulate the PSR's lighting and topological conditions, to which low light enhancement methods (CLAHE, Dehaze, RetinexNet, GLADNet) were applied to restore image brightness and color as well as to investigate their influences on the performance of feature extraction and matching methods (SIFT, SURF, ORB, AKAZE). The experiment results show that GLADNet and Dehaze images in order significantly improve image brightness and color. However, the performance of the feature extraction and matching methods were improved by Dehaze and GLADNet images in order, especially for ORB and AKAZE. Thus, in the lunar exploration, Dehaze is appropriate for building 3D topographic map whereas GLADNet is adequate for geological investigation.
Keywords
Lunar exploration; Permanently shadowed region; Low light image enhancement method; Feature extraction and matching method;
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Times Cited By KSCI : 3  (Citation Analysis)
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