By Topic

Detection and identification of effluent gases by long wave infrared (LWIR) hyperspectral images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sagiv, L. ; Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel ; Rotman, S.R. ; Blumberg, D.G.

Results will be presented concerning the development of an algorithm for the detection, identification and relative quantification of effluent gases emitted in industrial plume stacks using an LWIR hyperspectral remote sensing system. The technique consists of several steps, which are initialized by the localization of critical wavelengths in the spectral signatures and then their integration into an algorithm for the detection of high concentrated gas pixels in the image cube using a correlation coefficient metric. Further mapping of low concentrated pixels is carried out by an iterative Matched Filter (MF) method. Following the mapping of all the gases in the image cube, a least squares method was applied to derive gas content. The algorithm was tested on data cubes acquired in the bay of Haifa with chimneys emitting SO2 and CO2 gases from distances of 400 and 1700 m away; good results were obtained.

Published in:

Electrical and Electronics Engineers in Israel, 2008. IEEEI 2008. IEEE 25th Convention of

Date of Conference:

3-5 Dec. 2008