A New Approach to Unsupervised Target Classification for Polarimetric SAR Images

Xing RONG; Weijie ZHANG; Jian YANG; Wen HONG

doi:10.1093/ietcom/e91-b.6.2081

Regular Section

A New Approach to Unsupervised Target Classification for Polarimetric SAR Images

Xing RONG, Weijie ZHANG, Jian YANG, Wen HONG

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Keywords: polarimetric SAR, unsupervised classification, Inhomogeneous Markov Random Field, Graph Cuts

JOURNAL RESTRICTED ACCESS

2008 Volume E91.B Issue 6 Pages 2081-2084

DOI https://doi.org/10.1093/ietcom/e91-b.6.2081

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Abstract

A new unsupervised classification method is proposed for polarimetric SAR images to keep the spatial coherence of pixels and edges of different kinds of targets simultaneously. We consider the label scale variability of images by combining Inhomogeneous Markov Random Field (MRF) and Bayes' theorem. After minimizing an energy function using an expansion algorithm based on Graph Cuts, we can obtain classification results that are discontinuity preserving. Using a NASA/JPL AIRSAR image, we demonstrate the effectiveness of the proposed method.

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