Modified algorithm for mineral identification in LWIR hyperspectral imagery

Bardia Yousefi; Saeed Sojasi; Kévin Liaigre; Clemente Ibarra Castanedo; Georges Beaudoin; François Huot; Xavier P. V. Maldague; Martin Chamberland

doi:10.1117/12.2263090

5 May 2017 Modified algorithm for mineral identification in LWIR hyperspectral imagery

Bardia Yousefi, Saeed Sojasi, Kévin Liaigre, Clemente Ibarra Castanedo, Georges Beaudoin, François Huot, Xavier P. V. Maldague, Martin Chamberland

Author Affiliations +

Proceedings Volume 10214, Thermosense: Thermal Infrared Applications XXXIX; 102141H (2017) https://doi.org/10.1117/12.2263090
Event: SPIE Commercial + Scientific Sensing and Imaging, 2017, Anaheim, CA, United States

Abstract

The applications of hyperspectral infrared imagery in the different fields of research are significant and growing. It is mainly used in remote sensing for target detection, vegetation detection, urban area categorization, astronomy and geological applications. The geological applications of this technology mainly consist in mineral identification using in airborne or satellite imagery. We address a quantitative and qualitative assessment of mineral identification in the laboratory conditions. We strive to identify nine different mineral grains (Biotite, Diopside, Epidote, Goethite, Kyanite, Scheelite, Smithsonite, Tourmaline, Quartz). A hyperspectral camera in the Long Wave Infrared (LWIR, 7.7-11.8 ) with a LW-macro lens providing a spatial resolution of 100 μm, an infragold plate, and a heating source are the instruments used in the experiment. The proposed algorithm clusters all the pixel-spectra in different categories. Then the best representatives of each cluster are chosen and compared with the ASTER spectral library of JPL/NASA through spectral comparison techniques, such as Spectral angle mapper (SAM) and Normalized Cross Correlation (NCC). The results of the algorithm indicate significant computational efficiency (more than 20 times faster) as compared to previous algorithms and have shown a promising performance for mineral identification.

Citation Download Citation

Bardia Yousefi, Saeed Sojasi, Kévin Liaigre, Clemente Ibarra Castanedo, Georges Beaudoin, François Huot, Xavier P. V. Maldague, and Martin Chamberland "Modified algorithm for mineral identification in LWIR hyperspectral imagery", Proc. SPIE 10214, Thermosense: Thermal Infrared Applications XXXIX, 102141H (5 May 2017); https://doi.org/10.1117/12.2263090

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available