Abstract
There is difficulty for distinguishing of river and shadow in Synthetic Aperture Radar (SAR) images. A method of river segmentation in SAR images based on wavelet energy and gradient is proposed in this paper. It mainly includes two algorithms: coarse segmentation and refined segmentation. Firstly, The river regions are coarsely segmented by the wavelet energy feature, and then refined segmented accurately by the gradient threshold which is got adaptively. The experimental results show the validity of the method, which provides a good foundation for targets detection above the river.
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Support by the National Natural Science Foundation of China (NSFC) (No.60472072), the Specialized Research Foundation for the Doctoral Program of Higher Education (No.20040699034), the Aeronautical Science Foundation of China (No.05I53076), and the Yellow River Conservancy Commission (YRCC) Research on ecological improvement of the Yellow River (No.2004SZ01-04).
Communication author: Zhang Lili, born in 1982, female, master student.
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Zhang, L., Zhang, Y., Wang, M. et al. Adaptive river segmentation in SAR images. J. Electron.(China) 26, 438–442 (2009). https://doi.org/10.1007/s11767-007-0113-1
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DOI: https://doi.org/10.1007/s11767-007-0113-1