The ability to detect and identify gaseous effluents is a problem that has been pursued with limited success. It has been shown to bepossible using the Invariant algorithm on synthetic hyperspectralscenes with a strong single gas release. That however, is a veryspecific case and leaves room for further investigation. This studylooks at more realistic detection and release scenarios. Ourimplementation of the Invariant algorithm uses Singular ValueDecomposition (SVD) to select basis vectors from a subspace of targetgases in conjunction with a Generalized Likelihood Ratio Test (GLRT) to determine on a pixel by pixel basis how ``like" the target gas each pixel is. The target gases are modeled in the image radiance space including atmospheric effects. Target spectra are modeled in both emission and absorption. This study investigates how well weak plumes are detected. Also, there will be a test of a mixed gas in a strong plume release. Finally, a situation where a weak multiple gas release will be discussed. Synthetic hyperspectral imagery in the long wave infrared region (LWIR) of the electromagnetic spectrum will be the predominate data used in this study. This algorithm has been found to be applicable for these detection and identification scenarios.
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Erin M. O'Donnell, David W. Messinger, Carl Salvaggio, John R. Schott, "The invariant algorithm for identification and detection of multiple gas plumes and weak releases", Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.603940; https://doi.org/10.1117/12.603940
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