Background suppression and feature based spectroscopy methods for
sub-pixel material identification

Robert S. Rand; John M. Grossmann; Roger N. Clark; Eric Livo; J. Thomas Parr

doi:10.1117/12.930469

15 October 2012 Background suppression and feature based spectroscopy methods for sub-pixel material identification

Robert S. Rand, John M. Grossmann, Roger N. Clark, Eric Livo, J. Thomas Parr

Proceedings Volume 8515, Imaging Spectrometry XVII; 85150K (2012) https://doi.org/10.1117/12.930469
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

Feature-based imaging spectroscopy methods are effective for identifying materials that exhibit specific well-defined spectral absorption features. As long as a pixel contains a sufficient amount of material so that the absorption retains its predominant shape, a feature-based method can work well. However, there are occasions when a background material can mix with a material of interest, and significantly distort and maybe even remove the absorption. In such cases, the material identification capabilities of these methods are likely to be degraded. This effort proposes an approach to accommodate these conditions. The parameter values to determine fit of an absorption feature are selected to be more tolerant of distortions and the signal contributions of any detected sub-pixel backgrounds are removed by making use of a physically-constrained linear mixing model. This mixing model is used to remove any detected background spectra from the image spectra within the bounding locations of the spectral features. However, an expected consequence of loosening the parameter values and performing sub-pixel subtraction is an increase in false alarms. A statistically-based spectral matched filter is proposed as to reduce these false alarms. We test the individual and combined approaches for identifying full-pixel and sub-pixel Tyvek panels in an experiment using a HyMAP hyperspectral scene with ground truth collected over Waimanalo Bay, Oahu, Hawaii.

Citation Download Citation

Robert S. Rand, John M. Grossmann, Roger N. Clark, Eric Livo, and J. Thomas Parr "Background suppression and feature based spectroscopy methods for sub-pixel material identification", Proc. SPIE 8515, Imaging Spectrometry XVII, 85150K (15 October 2012); https://doi.org/10.1117/12.930469

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KEYWORDS

Absorption

Sensors

Single mode fibers

Optical filters

Hassium

Imaging spectroscopy

Spectroscopy

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