A Novel Method for Spectral Similarity Measure by Fusing Shape and Amplitude Features
Spectral similarity measure is the basis of spectral information extraction. The description of spectral features is the key to spectral similarity measure. To express the spectral shape and amplitude features reasonably, this paper presents the definition of shape and amplitude feature vector, co...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Eastern Macedonia and Thrace Institute of Technology
2015-12-01
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Series: | Journal of Engineering Science and Technology Review |
Subjects: | |
Online Access: | http://www.jestr.org/downloads/Volume8Issue5/fulltext85222015.pdf |
Summary: | Spectral similarity measure is the basis of spectral information extraction. The description of spectral features is the key
to spectral similarity measure. To express the spectral shape and amplitude features reasonably, this paper presents the
definition of shape and amplitude feature vector, constructs the shape feature distance vector and amplitude feature
distance vector, proposes the spectral similarity measure by fusing shape and amplitude features (SAF), and discloses the
relationship of fusing SAF with Euclidean distance and spectral information divergence. Different measures were tested
on the basis of United States Geological Survey (USGS) mineral_beckman_430. Generally, measures by integrating SAF
achieve the highest accuracy, followed by measures based on shape features and measures based on amplitude features.
In measures by integrating SAF, fusing SAF shows the highest accuracy. Fusing SAF expresses the measured results with
the inner product of shape and amplitude feature distance vectors, which integrate spectral shape and amplitude features
well. Fusing SAF is superior to other similarity measures that integrate SAF, such as spectral similarity scale, spectral
pan-similarity measure, and normalized spectral similarity score(NS3
). |
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ISSN: | 1791-2377 1791-2377 |