Identification and detection of gaseous effluents from hyperspectral imagery using invariant algorithms

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dc.contributor.author O'Donnell, Erin en_US
dc.contributor.author Messinger, David en_US
dc.contributor.author Salvaggio, Carl en_US
dc.contributor.author Schott, John en_US
dc.date.accessioned 2007-06-22T15:09:18Z en_US
dc.date.available 2007-06-22T15:09:18Z en_US
dc.date.issued 2004-04 en_US
dc.identifier.citation Proceedings of SPIE Sensor Data Exploitation and Target Recognition, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X 5425 (2004) 573-582 en_US
dc.identifier.issn 0277-786X en_US
dc.identifier.uri http://hdl.handle.net/1850/4061 en_US
dc.description "Identification and detection of gaseous effluents from hyperspectral imagery using invariant algorithms," Proceedings of the SPIE, Sensor Data Exploitation and Target Recognition, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, Vol. 5425. The International Society of Optical Engineers. Held in Orlando, Florida: April 2004. This paper is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. en_US
dc.description.abstract The ability to detect and identify effluent gases is, and will continue to be, of great importance. This would not only aid in the regulation of pollutants but also in treaty enforcement and monitoring the production of weapons. Considering these applications, finding a way to remotely investigate a gaseous emission is highly desirable. This research utilizes hyperspectral imagery in the infrared region of the electromagnetic spectrum to evaluate an invariant method of detecting and identifying gases within a scene. The image is evaluated on a pixel-by-pixel basis and is studied at the subpixel level. A library of target gas spectra is generated using a simple slab radiance model. This results in a more robust description of gas spectra which are representative of real-world observations. This library is the subspace utilized by the detection and identification algorithms. The subspace will be evaluated for the set of basis vectors that best span the subspace. The Lee algorithm will be used to determine the set of basis vectors, which implements the Maximum Distance Method (MaxD). A Generalized Likelihood Ratio Test (GLRT) determines whether or not the pixel contains the target. The target can be either a single species or a combination of gases. Synthetically generated scenes will be used for this research. This work evaluates whether the Lee invariant algorithm will be effective in the gas detection and identification problem. en_US
dc.description.sponsorship The Office of Naval Research Multi-disciplinary University Research Initiative ”Model-based Hyperspectral Exploitation Algorithm Development” no. N00014-01-1-0867 funded this project. en_US
dc.language.iso en_US en_US
dc.publisher The International Society for Optical Engineering (SPIE) en_US
dc.relation.ispartofseries vol. 5425 en_US
dc.subject Gaseous effluents en_US
dc.subject Hyperspectral imagery en_US
dc.subject Invariant algorithms en_US
dc.subject Plumes en_US
dc.subject Target detection en_US
dc.title Identification and detection of gaseous effluents from hyperspectral imagery using invariant algorithms en_US
dc.type Article en_US

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