TY - GEN
T1 - Parametric adaptive signal detection for hyperspectral imaging
AU - Li, Hongbin
AU - Michels, James H.
PY - 2006
Y1 - 2006
N2 - In this paper, we introduce a class at training-efficient adaptive signal detectors that exploit a parametric model taking into account the non-stationarity of H SI data in the spectral dimension. A maximum likelihood (ML) estimator is presented for estimation of the parameters associated with the proposed parametric model. Several important issues are discussed, including model order selection, training screening, and time-series based whitening and detection, which are intrinsic parts of the proposed parametric adaptive detectors. Experimental results using real HSI data reveal that the proposed parametric detectors are more training-efficient and outperform conventional covariance-matrix based detectors when the training size is limited.
AB - In this paper, we introduce a class at training-efficient adaptive signal detectors that exploit a parametric model taking into account the non-stationarity of H SI data in the spectral dimension. A maximum likelihood (ML) estimator is presented for estimation of the parameters associated with the proposed parametric model. Several important issues are discussed, including model order selection, training screening, and time-series based whitening and detection, which are intrinsic parts of the proposed parametric adaptive detectors. Experimental results using real HSI data reveal that the proposed parametric detectors are more training-efficient and outperform conventional covariance-matrix based detectors when the training size is limited.
UR - http://www.scopus.com/inward/record.url?scp=33947652723&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:33947652723
SN - 142440469X
SN - 9781424404698
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - V1197-V1200
BT - 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
T2 - 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Y2 - 14 May 2006 through 19 May 2006
ER -