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International Journal of Remote Sensing Volume 15, 1994 - Issue 11
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Original Articles

Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution

J. S. LEE Code 7230, Remote Sensing Division, Naval Research Laboratory, Washington, DC, 20375-5351, U.S.A.
,
M. R. GRUNES Code 7230, Remote Sensing Division, Naval Research Laboratory, Washington, DC, 20375-5351, U.S.A.
&
R. KWOK Code 7230, Remote Sensing Division, Naval Research Laboratory, Washington, DC, 20375-5351, U.S.A.
Pages 2299-2311 | Received 26 Mar 1993, Accepted 10 Aug 1993, Published online: 27 Apr 2007
 
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Abstract

Multi-look polarimetric SAR (synthetic aperture radar) data can be represented either in Mueller matrix form or in complex covariance matrix form. The latter has a complex Wishart distribution. A maximum likelihood classifier to segment polarimetric SAR data according to terrain types has been developed based on the Wishart distribution. This algorithm can also be applied to multifrequency multi-look polarimetric SAR data, as well as 10 SAR data containing only intensity information. A procedure is then developed for unsupervised classification.

The classification error is assessed by using Monte Carlo simulation of multilook polarimetric SAR data, owing to the lack of ground truth for each pixel. Comparisons of classification errors using the training sets and single-look data are also made. Applications of this algorithm are demonstrated with NASA/JPL P-, L- and C-band polarimetric SAR data.

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