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Classification Method for Fully PolSAR Data Based on Three Novel Parameters

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4 Author(s)
Shuang Zhang ; Key Lab. of Intell. Perception & Image Understanding, Xi'an, China ; Shuang Wang ; Bo Chen ; Shasha Mao

In this letter, a new classification method for fully polarimetric synthetic aperture radar (PolSAR) data based on three novel parameters is presented. The three parameters are derived from the eigenspace of the coherency matrix as linear combinations of its three eigenvalues. In the proposed classification method, the maximum value out of the three parameters is determined to assign a label to each image pixel, and the PolSAR image is classified into three classes accordingly. Experimental results based on NASA/JPL AIRSAR L-band data and CSA RADARSAT-2 C-band data illustrate the validity and efficacy of the procedure.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:11 ,  Issue: 1 )