首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Coastline Detection with Gaofen-3 SAR Images Using an Improved FCM Method
【2h】

Coastline Detection with Gaofen-3 SAR Images Using an Improved FCM Method

机译:利用改进的FCM方法用高分3 SAR图像进行海岸线检测

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The coastline detection is one of the main applications of the Gaofen-3 satellite in the ocean field. However, the capability of Gaofen-3 SAR image in coastline detection has not yet been validated. In this paper, two Gaofen-3 SAR images, acquired in 2016, were used to extract the coastlines of the regions of Bohai and Taihu in China, respectively. The classical Fuzzy C-means (FCM) method was used in the coastline detection, but had been improved by combining the Wavelet decomposition algorithm to better suppress the inherent speckle noises of SAR image. Coastline detection results obtained from two Sentinel-1 SAR images acquired on the same regions were compared with those of the Gaofen-3 images. By using the manually delineated coastlines as the standards in the qualitative evaluations, improvements of about 12.0%, 8.3%, 23.8%, and 9.4% can be achieved by the improved FCM method with respect to the indicators of mean, RMSE, PGSD, and P90%, respectively; demonstrating that the Gaofen-3 data is superior to the Sentinel-1 data in the detection of coastline.
机译:海岸线检测是高分三号卫星在海洋领域的主要应用之一。但是,高分3号SAR图像在海岸线检测中的能力尚未得到验证。本文使用2016年采集的两张高分3 SAR图像分别提取了中国渤海和太湖地区的海岸线。经典的模糊C均值(FCM)方法用于海岸线检测,但已结合小波分解算法进行了改进,以更好地抑制SAR图像的固有斑点噪声。将在相同区域获取的两个Sentinel-1 SAR图像获得的海岸线检测结果与Gaofen-3图像进行比较。通过使用人工划定的海岸线作为定性评估的标准,相对于均值,RMSE,PGSD和MSI指标,改进的FCM方法可以实现约12.0%,8.3%,23.8%和9.4%的改进。 P90%分别;表明在海岸线检测中,Gaofen-3数据优于Sentinel-1数据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号