Simplex ACE: a constrained subspace detector

Ziemann, Amanda; Theiler, James Patrick

doi:10.1117/1.OE.56.8.081808

Title: Simplex ACE: a constrained subspace detector

Journal Article · Thu Jun 15 00:00:00 EDT 2017 · Optical Engineering

DOI:https://doi.org/10.1117/1.OE.56.8.081808· OSTI ID:1460642

^[1];

^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

In hyperspectral target detection, one must contend with variability in both target materials and background clutter. While most algorithms focus on the background clutter, there are some materials for which there is substantial variability in the signatures of the target. When multiple signatures can be used to describe a target material, subspace detectors are often the detection algorithm of choice. However, as the number of variable target spectra increases, so does the size of the target subspace spanned by these spectra, which in turn increases the number of false alarms. Here in this paper, we propose a modification to this approach, wherein the target subspace is instead a constrained subspace, or a simplex without the sum-to-one constraint. We derive the simplex adaptive matched filter (simplex AMF) and the simplex adaptive cosine estimator (simplex ACE), which are constrained basis adaptations of the traditional subspace AMF and subspace ACE detectors. We present results using simplex AMF and simplex ACE for variable targets, and compare their performances against their subspace counterparts. Our primary interest is in the simplex ACE detector, and as such, the experiments herein seek to evaluate the robustness of simplex ACE, with simplex AMF included for comparison. Results are shown on hyperspectral images using both implanted and ground-truthed targets, and demonstrate the robustness of simplex ACE to target variability.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1460642

Report Number(s):: LA-UR-17-21174

Journal Information:: Optical Engineering, Vol. 56, Issue 8; ISSN 0091-3286

Publisher:: SPIECopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 11 works

Citation information provided by
Web of Science

References (45)

Hyperspectral target detection in a whitened space utilizing forward modeling concepts Ientilucci, Emmett J.; Bajorski, Peter 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) https://doi.org/10.1109/whispers.2010.5594939	conference	June 2010
Determination of trace-gas amounts in plumes by the use of orthogonal digital filtering of thermal-emission spectra Hayden, Andreas; Niple, Edward; Boyce, Bruce Applied Optics, Vol. 35, Issue 16 https://doi.org/10.1364/ao.35.002802	journal	January 1996
An Overview of Background Modeling for Detection of Targets and Anomalies in Hyperspectral Remotely Sensed Imagery Matteoli, Stefania; Diani, Marco; Theiler, James IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7, Issue 6 https://doi.org/10.1109/jstars.2014.2315772	journal	June 2014
A hybrid algorithm for subpixel detection in hyperspectral imagery Joshua Broadwater, Reuven Meth IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 https://doi.org/10.1109/igarss.2004.1370633	conference	January 2004
SpecTIR hyperspectral airborne Rochester experiment data collection campaign Herweg, Jared A.; Kerekes, John P.; Weatherbee, Oliver SPIE Defense, Security, and Sensing, SPIE Proceedings https://doi.org/10.1117/12.919268	conference	May 2012
The SHARE 2012 data campaign Giannandrea, AnneMarie; Raqueno, Nina; Messinger, David W. SPIE Defense, Security, and Sensing, SPIE Proceedings https://doi.org/10.1117/12.2015935	conference	May 2013
Performance of an adaptive detection algorithm; rejection of unwanted signals Kelly, E. J. IEEE Transactions on Aerospace and Electronic Systems, Vol. 25, Issue 2 https://doi.org/10.1109/7.18674	journal	March 1989
Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery Theiler, James; Scovel, Clint; Wohlberg, Brendt IEEE Geoscience and Remote Sensing Letters, Vol. 7, Issue 2 https://doi.org/10.1109/lgrs.2009.2032565	journal	April 2010
High-speed atmospheric correction for spectral image processing Perkins, Timothy; Adler-Golden, Steven; Cappelaere, Patrice SPIE Defense, Security, and Sensing, SPIE Proceedings https://doi.org/10.1117/12.918908	conference	May 2012
Unsupervised methods for the classification of hyperspectral images with low spatial resolution Villa, A.; Chanussot, J.; Benediktsson, J. A. Pattern Recognition, Vol. 46, Issue 6 https://doi.org/10.1016/j.patcog.2012.10.030	journal	June 2013
Infrared hyperspectral imaging results from vapor plume experiments Bennett, Charles L.; Carter, Michael R.; Fields, David J. SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, SPIE Proceedings https://doi.org/10.1117/12.210897	conference	June 1995
Hyperspectral Detection and Identification with Constrained Target Subspaces Adler-Golden, S.; Gruninger, J.; Sundberg, R. IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium https://doi.org/10.1109/igarss.2008.4779029	conference	July 2008
Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery Theiler, James; Foy, Bernard R.; Fraser, Andrew M. Defense and Security, SPIE Proceedings https://doi.org/10.1117/12.604075	conference	June 2005
Local spectral unmixing for target detection Ziemann, Amanda K. 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) https://doi.org/10.1109/ssiai.2016.7459179	conference	March 2016
Metrics of spectral image complexity with application to large area search Messinger, David W. Optical Engineering, Vol. 51, Issue 3 https://doi.org/10.1117/1.oe.51.3.036201	journal	March 2012
Detection Algorithms in Hyperspectral Imaging Systems: An Overview of Practical Algorithms Manolakis, Dimitris; Truslow, Eric; Pieper, Michael IEEE Signal Processing Magazine, Vol. 31, Issue 1 https://doi.org/10.1109/msp.2013.2278915	journal	January 2014
Survey of geometric and statistical unmixing algorithms for hyperspectral images Parente, Mario; Plaza, Antonio 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) https://doi.org/10.1109/whispers.2010.5594929	conference	June 2010
Spectral subspace matched filtering Schaum, Alan P. Aerospace/Defense Sensing, Simulation, and Controls, SPIE Proceedings https://doi.org/10.1117/12.436996	conference	August 2001
Hyperspectral detection and discrimination using the ACE algorithm Pieper, M. L.; Manolakis, D.; Lockwood, R. SPIE Optical Engineering + Applications, SPIE Proceedings https://doi.org/10.1117/12.893950	conference	September 2011
Very High Resolution Multiangle Urban Classification Analysis Longbotham, Nathan; Chaapel, Chuck; Bleiler, Laurence IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, Issue 4 https://doi.org/10.1109/tgrs.2011.2165548	journal	April 2012
Instance influence estimation for hyperspectral target signature characterization using extended functions of multiple instances Zou, Sheng; Zare, Alina SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2228154	conference	May 2016
A CFAR adaptive matched filter detector Robey, F. C.; Fuhrmann, D. R.; Kelly, E. J. IEEE Transactions on Aerospace and Electronic Systems, Vol. 28, Issue 1 https://doi.org/10.1109/7.135446	journal	January 1992
Graph-based and statistical approaches for detecting spectrally variable target materials Ziemann, Amanda K.; Theiler, James SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2224091	conference	May 2016
Right spectrum in the wrong place: a framework for local hyperspectral anomaly detection Theiler, James; Ziemann, Amanda K. Electronic Imaging, Vol. 2016, Issue 19 https://doi.org/10.2352/issn.2470-1173.2016.19.coimg-160	journal	February 2016
Rapid Convergence Rate in Adaptive Arrays Reed, I. S.; Mallett, J. D.; Brennan, L. E. IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-10, Issue 6 https://doi.org/10.1109/taes.1974.307893	journal	November 1974
Matched subspace detectors Scharf, L. L.; Friedlander, B. IEEE Transactions on Signal Processing, Vol. 42, Issue 8 https://doi.org/10.1109/78.301849	journal	January 1994
Detection and characterization of chemical vapor fugitive emissions by nonlinear optimal estimation: theory and simulation Gittins, Christopher M. Applied Optics, Vol. 48, Issue 23 https://doi.org/10.1364/ao.48.004545	journal	January 2009
Hybrid Detectors for Subpixel Targets Broadwater, Joshua; Chellappa, Rama IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, Issue 11 https://doi.org/10.1109/tpami.2007.1104	journal	November 2007
Enough with the additive target model Schaum, Alan SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2049146	conference	June 2014
Target detection assessment of the SHARE 2010/2012 hyperspectral data collection campaign Ientilucci, Emmett J. SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2177201	conference	May 2015
An adaptive locally linear embedding manifold learning approach for hyperspectral target detection Ziemann, Amanda K.; Messinger, David W. SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2177466	conference	May 2015
Strategies for Hyperspectral Target Detection In Complex Background Environments Eismann, M. T. 2006 IEEE Aerospace Conference https://doi.org/10.1109/aero.2006.1655905	conference	January 2006
Iterative convex hull volume estimation in hyperspectral imagery for change detection Ziemann, Amanda K.; Messinger, David W.; Basener, William F. SPIE Defense, Security, and Sensing, SPIE Proceedings https://doi.org/10.1117/12.850122	conference	April 2010
Invariant subpixel material detection in hyperspectral imagery Thai, B.; Healey, G. IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, Issue 3 https://doi.org/10.1109/tgrs.2002.1000320	journal	March 2002
Local background estimation and the replacement target model Theiler, James; Ziemann, Amanda SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2262833	conference	May 2017
Improved covariance matrices for point target detection in hyperspectral data Silverman, Jerry Optical Engineering, Vol. 47, Issue 7 https://doi.org/10.1117/1.2965814	journal	July 2008
Operational and Performance Considerations of Radiative-Transfer Modeling in Hyperspectral Target Detection Matteoli, Stefania; Ientilucci, Emmett J.; Kerekes, John P. IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, Issue 4 https://doi.org/10.1109/tgrs.2010.2081371	journal	April 2011
Continuum fusion: a theory of inference, with applications to hyperspectral detection Schaum, Alan Optics Express, Vol. 18, Issue 8 https://doi.org/10.1364/oe.18.008171	journal	January 2010
A parametric study of unsupervised anomaly detection performance in maritime imagery using manifold learning techniques Olson, C. C.; Doster, T. SPIE Defense + Security, SPIE Proceedings https://doi.org/10.1117/12.2227226	conference	May 2016
Quantitative reflectance spectra of solid powders as a function of particle size Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong Applied Optics, Vol. 54, Issue 15 https://doi.org/10.1364/AO.54.004863	journal	January 2015
Adaptive matched subspace detectors and adaptive coherence estimators Scharf, L. L.; McWhorter, L. T. Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers https://doi.org/10.1109/ACSSC.1996.599116	conference	January 1997
The adaptive coherence estimator: a uniformly most-powerful-invariant adaptive detection statistic Kraut, S.; Scharf, L. L.; Butler, R. W. IEEE Transactions on Signal Processing, Vol. 53, Issue 2 https://doi.org/10.1109/TSP.2004.840823	journal	February 2005
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches Bioucas-Dias, José M.; Plaza, Antonio; Dobigeon, Nicolas IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 5, Issue 2 https://doi.org/10.1109/JSTARS.2012.2194696	journal	April 2012
Development of a Web-Based Application to Evaluate Target Finding Algorithms Snyder, D.; Kerekes, J.; Fairweather, I. IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium https://doi.org/10.1109/IGARSS.2008.4779144	conference	July 2008
Matched subspace detectors Scharf, L. L.; Friedlander, B. Proceedings of 27th Asilomar Conference on Signals, Systems and Computers https://doi.org/10.1109/acssc.1993.342610	conference	January 1993

Similar Records

Improvements in the Method of Radiation Anomaly Detection by Spectral Comparison Ratios

Journal Article · Fri Apr 01 00:00:00 EDT 2016 · Applied Radiation and Isotopes · OSTI ID:1460642

Pfund, David M.; Anderson, K K.; Detwiler, Rebecca S.; +7 more

Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation

Journal Article · Thu Jun 11 00:00:00 EDT 2020 · Circuits, Systems, and Signal Processing · OSTI ID:1460642

Xiang, Yijian; Akcakaya, Murat; Sen, Satyabrata; +1 more

Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging

Technical Report · Tue Sep 21 00:00:00 EDT 2004 · OSTI ID:1460642

Clark, G A

Related Subjects

42 ENGINEERING
hyperspectral
target detection
target variability
adaptive cosine estimator
simplex ACE
subspace ACE

Title: Simplex ACE: a constrained subspace detector

Citation Formats

References (45)

Similar Records

Related Subjects