Beyond the adaptive matched filter: nonlinear detectors for weak signals in high-dimensional clutter
暂无分享,去创建一个
[1] Dimitris G. Manolakis,et al. Using elliptically contoured distributions to model hyperspectral imaging data and generate statistically similar synthetic data , 2004, SPIE Defense + Commercial Sensing.
[2] Edward J. Wegman,et al. Statistical Signal Processing , 1985 .
[3] Mario Winter,et al. N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data , 1999, Optics & Photonics.
[4] Alan P. Schaum,et al. Spectral subspace matched filtering , 2001, SPIE Defense + Commercial Sensing.
[5] Louis L. Scharf,et al. Adaptive subspace detectors , 2001, IEEE Trans. Signal Process..
[6] Marco Lops,et al. Asymptotically optimum radar detection in compound-Gaussian clutter , 1995 .
[7] Don H. Johnson,et al. Statistical Signal Processing , 2009, Encyclopedia of Biometrics.
[8] Dimitris G. Manolakis,et al. Taxonomy of detection algorithms for hyperspectral imaging applications , 2005 .
[9] Gerald S. Rogers,et al. Mathematical Statistics: A Decision Theoretic Approach , 1967 .
[10] Roger J. Combs,et al. Remote Detection of Heated Ethanol Plumes by Airborne Passive Fourier Transform Infrared Spectrometry , 2003, Applied spectroscopy.
[11] A. Schaum. Hyperspectral target detection using a Bayesian likelihood ratio test , 2002, Proceedings, IEEE Aerospace Conference.
[12] J. Boardman. Automating spectral unmixing of AVIRIS data using convex geometry concepts , 1993 .
[13] J. Boardman,et al. Mapping target signatures via partial unmixing of AVIRIS data: in Summaries , 1995 .
[14] James Theiler,et al. Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery , 2001, IEEE Trans. Geosci. Remote. Sens..
[15] E. Conte,et al. Adaptive matched filter detection in spherically invariant noise , 1996, IEEE Signal Processing Letters.
[16] James Theiler,et al. Resampling approach for anomaly detection in multispectral images , 2003, SPIE Defense + Commercial Sensing.
[17] Dimitris G. Manolakis,et al. Modeling hyperspectral imaging data , 2003, SPIE Defense + Commercial Sensing.
[18] John P. Kerekes,et al. Statistics of hyperspectral imaging data , 2001, SPIE Defense + Commercial Sensing.
[19] Steven C. Gustafson,et al. Johnson distribution models of hyperspectral image data clusters , 2006, SPIE Defense + Commercial Sensing.
[20] 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.
[21] A. Fraser,et al. Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery , 2005 .
[22] J. A. Gualtieri,et al. Support vector machines for classification of hyperspectral data , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).
[23] Thomas L. Ainsworth,et al. Exploiting manifold geometry in hyperspectral imagery , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[24] James Theiler,et al. Effect of signal contamination in matched-filter detection of the signal on a cluttered background , 2006, IEEE Geoscience and Remote Sensing Letters.
[25] A. Öztürk,et al. Non-Gaussian random vector identification using spherically invariant random processes , 1993 .
[26] J. Anthony Gualtieri,et al. Support vector machines for hyperspectral remote sensing classification , 1999, Other Conferences.
[27] R. Bellman,et al. V. Adaptive Control Processes , 1964 .
[28] E. J. Kelly. An Adaptive Detection Algorithm , 1986, IEEE Transactions on Aerospace and Electronic Systems.
[29] Beer. Bestimmung der Absorption des rothen Lichts in farbigen Flüssigkeiten , 1852 .
[30] Louis L. Scharf,et al. Matched subspace detectors , 1994, IEEE Trans. Signal Process..
[31] I. Reed,et al. Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.
[32] James Theiler,et al. Decision boundaries in two dimensions for target detection in hyperspectral imagery. , 2009, Optics express.
[33] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.