A Wavelet Neural Network for SAR Image Segmentation.
SENSORS 2009;
9:7509-15. [PMID:
22400005 PMCID:
PMC3290509 DOI:
10.3390/s90907509]
[Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2009] [Revised: 09/09/2009] [Accepted: 09/12/2009] [Indexed: 12/03/2022]
Abstract
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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