Image enhancement for UAV visual SLAM applications : analysis and evaluation
Tian, Yikun and Yue, Hong and Ren, Jinchang; Ren, Jinchang and Hussain, Amir and Liao, Iman Yi and Chen, Rongjun and Huang, Kaizhu and Zhao, Huimin and Liu, Xiaoyong and Ma, Ping and Maul, Thomas, eds. (2024) Image enhancement for UAV visual SLAM applications : analysis and evaluation. In: Advances in Brain Inspired Cognitive Systems. Lecture Notes in Computer Science . Springer, MYS, pp. 211-219. ISBN 9789819714179 (https://doi.org/10.1007/978-981-97-1417-9_20)
Text.
Filename: Tian-etal-Springer-2024-Image-enhancement-for-UAV-visual-SLAM-applications.pdf
Accepted Author Manuscript Restricted to Repository staff only until 22 May 2025. License: Strathprints license 1.0 Download (814kB) | Request a copy |
Abstract
Although simultaneous localisation and mapping (SLAM) has been widely applied in a wide range of robotics and navigation applications, its applicability is severely affected by the quality of the acquired images, especially for those in unmanned aerial vehicles (UAV). In this paper, comprehensive analysis and evaluation of the methods for enhancement of the UAV images are focused, especially the models for denoising of the UAV images using spatial-domain analysis, transform domain analysis and deep learning. Experiments on publicly available datasets are conducted for performance evaluation, along with both qualitative and quantitative results. Surprisingly, deep learning-based approaches did not perform particularly well as these did in other computer vision tasks such as object detection and recognition. Useful discussions are suggested how to further explore this interesting topic.
ORCID iDs
Tian, Yikun, Yue, Hong ORCID: https://orcid.org/0000-0003-2072-6223 and Ren, Jinchang; Ren, Jinchang, Hussain, Amir, Liao, Iman Yi, Chen, Rongjun, Huang, Kaizhu, Zhao, Huimin, Liu, Xiaoyong, Ma, Ping and Maul, Thomas-
-
Item type: Book Section ID code: 90144 Dates: DateEvent22 May 2024PublishedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 05 Aug 2024 15:26 Last modified: 11 Nov 2024 15:36 URI: https://strathprints.strath.ac.uk/id/eprint/90144