DLRW: Dual-Link Weight Random Walk Model for Aquaculture Boundary Extraction by Single-Polarized SAR Imagery
نویسندگان
چکیده
Coastal aquaculture is undertaken in shallow and usually sheltered waters along the coast, delineated by ponds. Illegal usage of coastal can lead to conflicts with local communities environmental problems. Thus, it necessary extract boundary monitor expansion sea. However, challenging for most existing algorithms synthetic aperture radar (SAR) images under a high incident angle (>30 degree) horizontal transmitted received (HH) or vertical (VV) polarization. The difficulties come from following: (1) seawater be seen on both sides such boundaries, (2) contrast boundaries uneven, (3) backscattering coefficients some parts are low. In this paper, novel dual-link weight random walk (DLRW)-based method proposed boundaries. DLRW composed an automatic seed points generation strategy, establishment solving model weight. By coarse-to-fine procedure, used whole imagery. Sentinel-1 GF-3 Dalian Liaodong Bay, China have been experiments. Mean offset (MO), root mean square error (RMSE), Overlapped, accuracy within one pixel (WOP), two pixels (WTP) evaluate performance methods. Experimental results demonstrated DLRW-based outperforms methods extraction Under low tide, better than other MO, RMSE, WOP, WTP at least 5.75 pixels, 10.43 2.88%, 11.09%, 18.04%, respectively. superior 3.8 10.5 6.3%. addition, has good ability shoreline bedrock, ports, silt. Therefore, great value monitoring, mapping, applications.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2023
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs15123109