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应用科学学报 >

2013 , Vol. 31 >Issue 1: 79 - 83

DOI: https://doi.org/10.3969/j.issn.0255-8297.2013.01.013

信号与信息处理

GIS数据约束的海岸带SAR图像多尺度分割

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  • 1. 中国科学院数字地球重点实验室，北京100094
    2. 中国科学院对地观测与数字地球科学中心，北京100094
朱俊杰，博士，副研究员，研究方向：遥感图像处理，E-mail: jjzhu@ceode.ac.cn；范湘涛，研究员，博导，研究方向：遥感与数字地球，E-mail：xtfan@ceode.ac.cn；郭华东，院士，博导，研究方向：雷达遥感，E-mail: hdguo@ceode.ac.cn

收稿日期: 2011-09-02

  修回日期: 2011-12-08

  网络出版日期: 2012-02-08

基金资助

国家自然科学基金(No.41071274, No.61132006)资助

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GIS-Constrained Multi-scale Coastal SAR Image Segmentation

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  • 1. Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing 100094, China
    2. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Received date: 2011-09-02

  Revised date: 2011-12-08

  Online published: 2012-02-08

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摘要

针对海岸带区域地理信息系统(geographic information system, GIS)矢量数据和合成孔径雷达(synthetic aperture radar, SAR)图像所表达信息的不同，探讨多尺度GIS矢量数据约束下的高分辨率SAR图像多尺度割. 在县级GIS矢量数据约束下，利用分形网络演化分割方法对高分辨率SAR图像进行分割，得到第1层分割结果. 然后在省级GIS矢量数据约束下，对第1层分割结果进行聚合，得到第2层分割结果. 该方法既能实现GIS矢量数据约束下的高分辨率SAR图像多尺度分割，获得满足GIS矢量数据约束和根据后向散射特征聚合的多尺度分割结果，又能消除瞬时SAR图像海岸线不确定的不足. 利用一幅天津地区的SAR图像进行实验，证实了该方法是一种有意义的图像多尺度分割方法，且得到的分割结果可用于有特定需求的图像分析和统计.

关键词： 遥感; 地理信息系统; 合成孔径雷达; 多尺度; 分割; 海岸带

本文引用格式

朱俊杰1,2， 杜小平1,2， 范湘涛1,2， 郭华东1,2 . GIS数据约束的海岸带SAR图像多尺度分割[J]. 应用科学学报, 2013 , 31(1) : 79 -83 . DOI: 10.3969/j.issn.0255-8297.2013.01.013

Abstract

Both geographic information system (GIS) data and remote sensing imagery are spatial data with multi-scale features although they are concerned with different types of information. This paper discusses the multi-scale segmentation of high-resolution synthetic aperture radar (SAR) images near coastal zones constrained by GIS vector data. To obtain the first level segmentation results at the county-level scale, the high-resolution SAR image is segmented using the fractal network evolution method with the constraint of GIS data. Then, at the province-level scale, the first level results are aggregated to obtain the second level segmentation results. This segmentation results satisfy both the constraint of GIS vector data and the scattering characteristics of SAR images. False coastlines in the SAR images are eliminated. Experimental results show that the proposed method is effective, and the segmentation results can be used for further image statistics and analyses.

Key words： multi-scale; segmentation; coastal zone; remote sensing; geographic information system (GIS); synthetic aperture radar (SAR)

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