Title :
Unsupervised classification of PolInSAR image based on Shannon Entropy Characterization
Author :
Yan, Wei ; Yang, Wen ; Liu, Ying ; Sun, Hong
Author_Institution :
Sch. of Electron. Inf., Wuhan Univ., Wuhan, China
Abstract :
In this paper, we propose a new method for unsupervised classification of polarimetric synthetic aperture radar interferometry (PolInSAR) images based on Shannon Entropy Characterization. Firstly, we use polarimetric H (entropy) and a parameters to classify the image initially. Then, we reclassify the image according to the span of Shannon Entropy Characterization. Finally, we fuse the results of the two previous steps and merge them to the specified number of clusters. The effectiveness of this method is demonstrated on CETC38 PolInSAR data and E-SAR PolInSAR data.
Keywords :
information theory; radar imaging; radar interferometry; synthetic aperture radar; CETC38 PolInSAR data; E-SAR PolInSAR data; Shannon entropy characterization; polarimetric H parameters; polarimetric synthetic aperture radar interferometry images; unsupervised classification; Airports; Covariance matrix; Entropy; Interferometry; Pixel; Remote sensing; Scattering; PolInSAR; Shannon entropy; complex Wishart; unsupervised classiflcation;
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
DOI :
10.1109/ICOSP.2010.5656856
