测绘学报 ›› 2019, Vol. 48 ›› Issue (4): 439-447.doi: 10.11947/j.AGCS.2019.20170732

• 摄影测量学与遥感 • 上一篇    下一篇

结合先验概率估计的GF-3影像水体概率估计方法

孟令奎1,2, 毛旭东1, 魏祖帅1, 张文1   

  1. 1. 武汉大学遥感信息工程学院, 湖北 武汉 430079;
    2. 地球空间信息技术协同创新中心, 湖北 武汉 430079
  • 收稿日期:2017-12-20 修回日期:2018-08-24 出版日期:2019-04-20 发布日期:2019-05-15
  • 通讯作者: 张文 E-mail:wen_zhang@whu.edu.cn
  • 作者简介:孟令奎(1967-),男,教授,研究方向为网络GIS、水利遥感技术及应用。E-mail:lkmeng@whu.edu.cn
  • 基金资助:
    国家重点研发计划(2017YFC0405806)

Probabilistic water body mapping of GF-3 images based on prior probability estimation

MENG Lingkui1,2, MAO Xudong1, WEI Zushuai1, ZHANG Wen1   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
    2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
  • Received:2017-12-20 Revised:2018-08-24 Online:2019-04-20 Published:2019-05-15
  • Supported by:
    The National Key Research and Development Program of China (No. 2017YFC0405806)

摘要: 综合SAR(synthetic aperture radar)影像的统计模型假设与k-means聚类算法,提出了一种结合水体分布先验概率估计的水体概率估计方法。首先,用贝叶斯推断对研究区域后向散射系数做统计模型假设。随后,结合聚类算法对像元作分类,估计水体分布先验概率,结合统计分布直方图使用非线性最小二乘拟合完成模型参数估计。试验选取了高分三号(GF-3)多种工作模式数据,并用高分一号(GF-1)影像进行验证。结果表明,该方法可有效实现SAR影像的高精度水体概率估计。

关键词: 水体概率估计, 参数估计, 合成孔径雷达(SAR), 高分三号

Abstract: We combine k-means cluster algorithm with the statistical model of SAR(synthetic aperture radar) images and develop the probabilistic water body mapping algorithm based on the priori probability estimation. Firstly, we make the statistical model assumption about backscatter values based on Bayesian theory. Then, we classify the images based on cluster algorithm, calculate the prior probability of the water body mapping and estimate the parameters of the statistical model of water distribution.Thewater body probabilistic maps based on GF-3 images in Luquan and Xianning are calculated and then validated with GF-1 images. The algorithm is effective on high-precision probabilistic water body mapping of SAR images.

Key words: probabilistic water body mapping, parameter estimation, synthetic aperture radar (SAR), GF-3

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