Segmented regression for spatio-spectral background estimation
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[1] John P. Kerekes,et al. Statistics of hyperspectral imaging data , 2001, SPIE Defense + Commercial Sensing.
[2] Yuval Cohen,et al. Subpixel hyperspectral target detection using local spectral and spatial information , 2012 .
[3] James Theiler,et al. Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery , 2010, IEEE Geoscience and Remote Sensing Letters.
[4] I. Reed,et al. Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.
[5] James Theiler,et al. Regression framework for background estimation in remote sensing imagery , 2013, 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).
[6] James Theiler,et al. EC-GLRT: Detecting Weak Plumes in Non-Gaussian Hyperspectral Clutter Using an Elliptically-Contoured Generalized Likelihood Ratio Test , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.
[7] Giovanni B. Marchisio,et al. WorldView-2 and the evolution of the DigitalGlobe remote sensing satellite constellation: introductory paper for the special session on WorldView-2 , 2012, Defense + Commercial Sensing.
[8] L.L. Scharf,et al. Adaptive matched subspace detectors and adaptive coherence estimators , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.
[9] C. Borel. Methods to find sub-pixel targets in hyperspectral data , 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).
[10] Xiaoli Yu,et al. Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution , 1990, IEEE Trans. Acoust. Speech Signal Process..
[11] James Theiler,et al. Ellipsoids for anomaly detection in remote sensing imagery , 2015, Defense + Security Symposium.
[12] David A. Landgrebe,et al. Signal Theory Methods in Multispectral Remote Sensing , 2003 .
[13] Stanley R. Rotman,et al. Evaluating backgrounds for subpixel target detection: when closer isn't better , 2015, Defense + Security Symposium.
[14] Yuval Cohen,et al. Evaluating Subpixel Target Detection Algorithms in Hyperspectral Imagery , 2012, J. Electr. Comput. Eng..
[15] James Theiler,et al. Right spectrum in the wrong place: a framework for local hyperspectral anomaly detection , 2016, Computational Imaging.
[16] S.R. Rotman,et al. Improved covariance matrices for point target detection in hyperspectral data , 2008, 2009 IEEE International Conference on Microwaves, Communications, Antennas and Electronics Systems.
[17] James Theiler,et al. Symmetrized regression for hyperspectral background estimation , 2015, Defense + Security Symposium.
[18] Marcus S. Stefanou,et al. Analysis of false alarm distributions in the development and evaluation of hyperspectral point target detection algorithms , 2007 .
[19] John P. Kerekes,et al. Development of a Web-Based Application to Evaluate Target Finding Algorithms , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.
[20] S. Rotman,et al. Spatial-spectral filtering for the detection of point targets in multi- and hyperspectral data , 2005 .
[21] Christoph C. Borel,et al. Improving the detectability of small spectral targets through spatial filtering , 2010, Optical Engineering + Applications.
[22] Stefania Matteoli,et al. An Overview of Background Modeling for Detection of Targets and Anomalies in Hyperspectral Remotely Sensed Imagery , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.