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GAS DETECTION BY USING TRANSMITTANCE ESTIMATION AND SEGMENTATION APPROACHES
Date
2016-09-27
Author
Başkurt, Nur Didem
Gur, Yusuf
Omruuzun, Fatih
Çetin, Yasemin
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Hyperspectral imaging for gas detection applications is an under-researched topic. The same gas model is used in most of the gas detection studies in the literature. This model aims to formulate the scene covering the gas emission as well as the background and the atmosphere. Therefore, the model requires prior knowledge on transmittance, emissivity, and temperature values of the components in the scene. The commonly used approaches to estimate these parameters include atmospheric modeling and statistical inference. However, accessing such information is costly in remote detection applications. Some studies avoid background characterization by decomposing the scene using spectral-spatial information.
Subject Keywords
Gas detection
,
Remote sensing;
,
Hyperspectral imaging
URI
https://hdl.handle.net/11511/57148
DOI
https://doi.org/10.1117/12.2242111
Collections
Graduate School of Informatics, Conference / Seminar
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N. D. Başkurt, Y. Gur, F. Omruuzun, and Y. Çetin, “GAS DETECTION BY USING TRANSMITTANCE ESTIMATION AND SEGMENTATION APPROACHES,” 2016, vol. 10008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57148.