Iterative approach for gas detection and identification

An iterative algorithm which identifies the presence of different gases throughout a hyperspectral cube was developed and tested. The algorithm uses the “stepwise regression” method combined with new methods of detection and identification in the hyperspectral cube´s analysis. This algorithm begins with a library of gas signatures; an initial fit is done with all the gases. The algorithm then eliminates those signatures which do not noticeably improve the fit to the measured signature. A necessary post-processing step eliminates gases which are not uniquely fit to the signature of the examined pixel.