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Multiscale probabilistic neural network method for SAR image segmentation
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DOI：10.1016/j.amc.2008.05.030.png)
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This paper proposes an effective multiscale method for the segmentation of the synthetic aperture radar (SAR) images via probabilistic neural network. By combining the probabilistic neural network (PNN) with the multiscale autoregressive (MAR) model, a classifier, which inherits the excellent strongpoint from both of them, is designed. The MAR models are utilized to extract the multiscale feature of SAR image, which is the input of the network. The PNN is trained by the proposed algorithm, and then the SAR images are segmented by the trained network. The experimental result demonstrates the effectiveness and efficiency of the proposed method. (C) 2008 Elsevier Inc. All rights reserved.
Keyword:
Multiscale autoregressive model
Probabilistic neural network
Synthetic aperture radar
Image segmentation
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
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