Open AccessEnriching absorption features for hyperspectral materials identification
Author(s) -
Baofeng Guo
Publication year - 2020
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.384580
Subject(s) - hyperspectral imaging , identification (biology) , absorption (acoustics) , remote sensing , orientation (vector space) , computer science , artificial intelligence , optics , representation (politics) , full spectral imaging , pattern recognition (psychology) , materials science , mathematics , physics , geology , botany , geometry , politics , law , political science , biology
Many materials have certain unique 'spectral fingerprints' in electromagnetic spectrum, which enables identification of materials based on hyperspectral imaging technique. In this paper, besides using the location information of absorptions, we propose to extract a group of real-valued parameters based on a detected absorption valley. These absorption parameters are chosen to characterize the details of the spectral absorption quantitatively, and are measured without human intervention. Moreover, we design an orientation descriptor to explore the local characterization for the shape representation of a hyperspectral absorption. According to the idea of information fusion, the augmentation of the absorption parameters and the orientation descriptor may increase the discriminatory ability and lead to an improved hyperspectral material identification. Simulations of material identification accuracy were carried out on two hyperspectral data sets, including a 7 classes of materials from ASD sensor, and a 16 classes of vegetation data from the AVIRIS 92AV3C. Results conclude the effectiveness of the method, which increases the identification accuracy compared to two classical approaches.