A New Approach to Unsupervised Target Classification for Polarimetric SAR Images
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2008-06-01
著者
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Yang Jian
Tsinghua Univ. Beijing Chn
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Zhang Weijie
Dept. Of Electronic Eng. Tsinghua University
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Yang Jian
Dept. Of Electronic Eng. Tsinghua University
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RONG Xing
Dept. of Electronic Eng., Tsinghua University
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HONG Wen
National Key Lab of Microwave Imaging Technology, Institute of Electronics
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Hong Wen
National Key Lab Of Microwave Imaging Technology Institute Of Electronics
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Rong Xing
Dept. Of Electronic Eng. Tsinghua University
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