GAS DETECTION BY USING TRANSMITTANCE ESTIMATION AND SEGMENTATION APPROACHES

Date

2016-09-27

Author

Başkurt, Nur Didem
Gur, Yusuf
Omruuzun, Fatih
Çetin, Yasemin

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This work is licensed under a 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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Citation Formats

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.