Ground-level temperature-emissivity based contrast enhancement with uncooled multiband LWIR cameras
Affiliation
Wyant College of Optical Sciences, University of ArizonaIssue Date
2021
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SPIECitation
Grimming, R., Driggers, R., Renshaw, K., & Furxhi, O. (2021). Ground-level temperature-emissivity based contrast enhancement with uncooled multiband LWIR cameras. Proceedings of SPIE - The International Society for Optical Engineering, 11740.Rights
Copyright © 2021 SPIE.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Optimal longwave infrared (LWIR) scene contrast occurs when reflections from other sources are minimized, leaving only thermal emission. Applying contrast enhancement to LWIR imagery based on pixel values' spatial distribution without regard to underlying temperature and emissivity is a non-physics-based approach. For a physics-based approach, something must be known about the temperature or the objects' emissivity under observation. In remote sensing applications, atmospheric conditions are measured allowing for calculated values for downwelling and path radiance to be obtained. Then, an iterative process can be performed using well-established TES algorithms to determine temperature and emissivity within specific bands. In this paper, we propose a method using a three-band LWIR imaging system with a partial sky view to collect in-scene data to apply contrast enhancement based on spectral differences between bands. Unlike traditional contrast enhancement methods, temperature variations between each band are considered and implemented using relatively inexpensive uncooled microbolometer cameras. We detail the process used for calibrating and determining brightness temperatures with sub-band LWIR filtered cameras. Using absolute sky radiance correlated to MODTRAN6 models, we estimate objects' emissivity profiles in a scene and propose an algorithm for applying contrast enhancement. © 2021 SPIE.Note
Immediate accessISSN
0277-786XISBN
9781510643178Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1117/12.2587176