Paper Info
Title
Automated Labeling of Materials in Hyperspectral Imagery
Abstract
We present a technique for automatically labeling segmented hyperspectral imagery with semantically meaningful material labels. The technique compares the mean signatures of each image segment to a spectral library of known materials, and material labels are assigned to image segments according to the most similar library entry. The similarity between spectral signatures is evaluated using our recently proposed CICRd similarity measure designed specifically for hyperspectral imagery. This measure considers both the continuum-intact reflectance spectrum and its continuum-removed representation. We provide a thorough assessment of this measure by comparison to several commonly used similarity measures on a well-studied low-altitude Airborne Visible/Infrared Imaging Spectrometer image of an urban area. We evaluate our results using both information-theoretic techniques and visual validation of the resulting spectral matches.
Year
DOI
Venue
2010
10.1109/TGRS.2010.2052815
Geoscience and Remote Sensing, IEEE Transactions
Keywords
Field
DocType
geophysical image processing,geophysical techniques,image segmentation,Airborne Visible/Infrared Imaging Spectrometer image,CICRd similarity measure,automated labeling,continuum-intact reflectance spectrum,continuum-removed representation,hyperspectral imagery,image segments,information-theoretic techniques,material labels,spectral matching,spectral signatures,Airborne Visible/Infrared Imaging Spectrometer (AVIRIS),automatic labeling,hyperspectral imagery,material labeling,spectral matching,urban
Computer vision,Imaging spectrometer,Similarity measure,Remote sensing,Image segmentation,Hyperspectral imaging,Artificial intelligence,Reflectivity,Spectral matching,Spectral signature,Mathematics
Journal
Volume
Issue
ISSN
48
11
0196-2892
Citations 
PageRank 
References 
3
0.66
9
Authors
3
Name
Order
Citations
PageRank
Brian David Bue130.66
Erzsébet Merényi218015.63
Beáta Csathó3132.77