DocumentCode :
2105459
Title :
Optimal polarimetric decomposition variables-non-linear dimensionality reduction
Author :
Ainsworth, T.L. ; Lee, J.S.
Author_Institution :
Remote Sensing Div., Naval Res. Lab., Washington, DC, USA
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
928
Abstract :
Polarimetric SAR image analysis often depends upon proper identification of the relevant degrees of freedom for the problem at hand. Employing physical models of particular scattering processes simplifies identification of the appropriate polarimetric variables. Determining how well variables chosen on the basis of a particular model describe the region of applicability of that model is difficult. Here we attempt in a model independent manner to identify "optimal" variables to both segment an image and highlight the variation within each segment. The method presently employed is non-linear dimensionality reduction
Keywords :
image segmentation; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; degrees of freedom; nonlinear dimensionality reduction; optimal polarimetric decomposition variables; polarimetric SAR image analysis; polarimetric variables; scattering processes; segmentation; Cost function; Covariance matrix; Entropy; Geometry; Image analysis; Image segmentation; Laboratories; Polarization; Remote sensing; Scattering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
Type :
conf
DOI :
10.1109/IGARSS.2001.976683
Filename :
976683
Link To Document :
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