A Wavelet Neural Network for SAR Image Segmentation
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Key Laboratory of Computer Vision and System of Ministry of Education, Tianjin University of Technology, Tianjin 300191, China
2
Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin, 300191, China
*
Author to whom correspondence should be addressed.
Sensors 2009, 9(9), 7509-7515; https://doi.org/10.3390/s90907509
Received: 29 July 2009
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Revised: 9 September 2009
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Accepted: 12 September 2009
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Published: 22 September 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
This paper proposes a wavelet neural network (WNN) for SAR image segmentation by combining the wavelet transform and an artificial neural network. The WNN combines the multiscale analysis ability of the wavelet transform and the classification capability of the artificial neural network by setting the wavelet function as the transfer function of the neural network. Several SAR images are segmented by the network whose transfer functions are the Morlet and Mexihat functions, respectively. The experimental results show the proposed method is very effective and accurate.
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MDPI and ACS Style
Wen, X.-B.; Zhang, H.; Wang, F.-Y. A Wavelet Neural Network for SAR Image Segmentation. Sensors 2009, 9, 7509-7515. https://doi.org/10.3390/s90907509
AMA Style
Wen X-B, Zhang H, Wang F-Y. A Wavelet Neural Network for SAR Image Segmentation. Sensors. 2009; 9(9):7509-7515. https://doi.org/10.3390/s90907509
Chicago/Turabian StyleWen, Xian-Bin, Hua Zhang, and Fa-Yu Wang. 2009. "A Wavelet Neural Network for SAR Image Segmentation" Sensors 9, no. 9: 7509-7515. https://doi.org/10.3390/s90907509
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