Title :
A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data
Author :
Conradsen, Knut ; Nielsen, Allan Aasbjerg ; Schou, Jesper ; Skriver, Henning
Author_Institution :
Informatics & Math. Modelling, Tech. Univ. of Denmark, Lyngby, Denmark
fDate :
1/1/2003 12:00:00 AM
Abstract :
When working with multilook fully polarimetric synthetic aperture radar (SAR) data, an appropriate way of representing the backscattered signal consists of the so-called covariance matrix. For each pixel, this is a 3×3 Hermitian positive definite matrix that follows a complex Wishart distribution. Based on this distribution, a test statistic for equality of two such matrices and an associated asymptotic probability for obtaining a smaller value of the test statistic are derived and applied successfully to change detection in polarimetric SAR data. In a case study, EMISAR L-band data from April 17, 1998 and May 20, 1998 covering agricultural fields near Foulum, Denmark are used. Multilook full covariance matrix data, azimuthal symmetric data, covariance matrix diagonal-only data, and horizontal-horizontal (HH), vertical-vertical (VV), or horizontal-vertical (HV) data alone can be used. If applied to HH, VV, or HV data alone, the derived test statistic reduces to the well-known gamma likelihood-ratio test statistic. The derived test statistic and the associated significance value can be applied as a line or edge detector in fully polarimetric SAR data also.
Keywords :
geophysical signal processing; geophysical techniques; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; terrain mapping; vegetation mapping; Denmark; EMISAR; Foulum; Hermitian positive definite matrix; L -band; agricultural fields; backscattered signal; change detection; complex Wishart distribution; covariance matrix; geophysical measurement technique; land surface; polarimetric SAR; radar polarimetry; radar remote sensing; radar scattering; radar theory; synthetic aperture radar; terrain mapping; test statistic; vegetation mapping; Covariance matrix; Detectors; L-band; Polarimetric synthetic aperture radar; Probability; Radar detection; Statistical analysis; Statistical distributions; Synthetic aperture radar; Testing;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2002.808066