基于快速异源配准的高分辨率SAR影像海岛区域正射校正

向俞明 滕飞 王林徽 焦念刚 王峰 尤红建

向俞明, 滕飞, 王林徽, 等. 基于快速异源配准的高分辨率SAR影像海岛区域正射校正[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24022
引用本文: 向俞明, 滕飞, 王林徽, 等. 基于快速异源配准的高分辨率SAR影像海岛区域正射校正[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24022
XIANG Yuming, TENG Fei, WANG Linhui, et al. Orthorectification of high-resolution SAR images in island regions based on fast multimodal registration[J]. Journal of Radars, in press. doi: 10.12000/JR24022
Citation: XIANG Yuming, TENG Fei, WANG Linhui, et al. Orthorectification of high-resolution SAR images in island regions based on fast multimodal registration[J]. Journal of Radars, in press. doi: 10.12000/JR24022

基于快速异源配准的高分辨率SAR影像海岛区域正射校正

doi: 10.12000/JR24022
基金项目: 中国科学院前沿科学重点研究计划(ZDBS-LY-JSC036),国家自然科学基金(61901439)
详细信息
    作者简介:

    向俞明,博士,副研究员,主要研究方向为SAR影像配准、异源遥感影像配准、遥感影像三维重建

    滕 飞,博士,助理研究员,主要研究方向为SAR成像处理与信息提取

    王林徽,博士生,主要研究方向为雷达图像解译、卫星图像边缘计算

    焦念刚,博士,助理研究员,主要研究方向为遥感影像几何处理

    王 峰,博士,副研究员,研究方向为多源遥感影像精细化处理

    尤红建,博士,研究员,主要研究方向为SAR影像配准、遥感影像几何精准处理等

    通讯作者:

    向俞明 xiangym@aircas.ac.cn

  • 责任主编:毕辉 Corresponding Editor: BI Hui
  • 11 数据来源于天仪遥感数据中心 https://data.spacety.com
  • 中图分类号: TP751

Orthorectification of High-resolution SAR Images in Island Regions Based on Fast Multimodal Registration

Funds: Key Research Program of Frontier Sciences, Chinese Academy of Sciences (ZDBS-LY-JSC036), The National Natural Science Foundation of China (61901439)
More Information
  • 摘要: 随着高分辨率合成孔径雷达(SAR)卫星的陆续发射,对天气条件多变的海岛区域进行全天候、全时段的高精度观测已变得可行。作为多种遥感应用的关键前置步骤正射校正,依赖于高精度控制点来纠正SAR影像的几何定位误差。然而,在海岛区域获取符合SAR校正要求的人工控制点不仅成本高,且风险大。为了应对这一挑战,该文首先提出了一种光学与SAR异源影像的快速配准算法,然后基于光学参考底图自动提取控制点,实现了海岛区域SAR影像的正射校正。所提出的配准算法分为两个阶段:首先构建异源影像的共性密集特征,然后在降采样后的特征上进行逐像素匹配,避免了异源影像特征点重复性低的问题。为了降低匹配复杂度,引入了海陆分割掩模以限定搜索范围。接着,对初步匹配点进行局部精细匹配,以减少降采样带来的不准确性。同时,引入海岸线均匀采样点以提升匹配结果的均匀性,并通过分段线性变换模型生成正射影像,确保了稀疏岛屿区域的整体校正精度。该算法在多景海岛区域的高分辨率SAR影像上表现出色,平均定位误差为3.2 m,整景校正时间仅需17.3 s,均优于现有多种先进的异源配准与校正算法,显示出其在工程应用中的巨大潜力。

     

  • 图  1  海岛区域SAR影像与光学底图的海岸线对比展示(黄线为OpenStreetMap开源海岸线矢量)

    Figure  1.  The comparison display of coastlines between SAR images of island regions and optical base maps (the yellow line delineates the coastline obtained form OpenStreetMap)

    图  2  海岛区域SAR影像与光学底图的辐射对比展示

    Figure  2.  The radiance comparison display between SAR images of island regions and optical base maps

    图  3  本文所提双阶段配准及正射校正方法的算法流程图

    Figure  3.  The algorithm flowchart of the two-stage registration and orthorectification method mentioned in this paper

    图  4  海岛区域SAR影像与光学底图海陆掩模结果

    Figure  4.  The land-sea mask results of SAR images and optical base maps in island regions

    图  5  原始分段线性变换与结合海岸线采样点的分段线性变换对比结果

    Figure  5.  Comparison results between the original piecewise linear transformation and the piecewise linear transformation combined with coastline sampling points

    图  6  4个测试区域的待纠正SAR影像和光学底图(底图上的绿点代表人工选取的基准点,均匀分布在图中的显著区域)

    Figure  6.  The SAR images to be corrected and the optical base maps for four test areas (the green dots on the base maps represent manually selected reference points, evenly distributed across the significant areas of the images)

    图  7  所有算法在6组测试影像上的匹配点数量和全流程处理时间

    Figure  7.  The number of matching points and the total processing time for all algorithms on six sets of test images

    图  8  4个测试区域对比算法的匹配点分布结果(仅展示了在光学底图上的位置)

    Figure  8.  The distribution results of matching points for the comparison algorithms in four test areas (only showing the positions on the optical base maps)

    图  9  测试区域A1的匹配校正结果展示

    Figure  9.  The display of the matching and rectification results for test area A1

    图  10  测试区域B的匹配校正结果展示

    Figure  10.  The display of the matching and rectification results for test area B

    图  11  测试区域C的匹配校正结果展示

    Figure  11.  The display of the matching and rectification results for test area C

    图  12  测试区域D的匹配校正结果展示

    Figure  12.  The display of the matching and rectification results for test area D

    图  13  开源海岸线矢量与海陆分割结果的对比显示

    Figure  13.  The comparison between open-source coastline vectors and land-sea segmentation results

    表  1  待校正的SAR影像成像参数信息

    Table  1.   The imaging parameter information of the SAR image to be rectified

    测试区域卫星型号成像模式成像视角(°)波段采样间隔(m)影像尺寸(像素)
    A1高分三号滑动聚束41.2C0.56/0.3615616×29344
    A2高分三号滑动聚束21.4C0.56/0.318635×33560
    B高分三号滑动聚束39.3C0.56/0.3413660×32208
    C高分三号滑动聚束29.7C0.56/0.3310946×32032
    D1海丝一号滑动聚束28.0C0.31/0.179188×45875
    D2海丝一号滑动聚束28.8C0.31/0.3212748×22937
    下载: 导出CSV

    表  2  所有算法在6组测试影像上的定位误差(m)

    Table  2.   The positioning errors of all algorithms on six sets of test images (m)

    方法 A1 A2 B C D1 D2 平均处理时间(s)
    本文算法 1.82 2.98 3.65 5.50 2.81 2.45 17.3
    SFOC 2.10 / / 15.20 3.88 3.43 139.8
    RIFT 2.93 3.87 7.09 6.54 5.90 4.33 194.3
    3MRS 2.02 4.15 5.51 12.68 6.15 3.59 160.7
    海岸线匹配 8.71 / / 9.44 12.15 6.04 172.1
    注:/代表校正失败。
    下载: 导出CSV

    表  3  消融实验方法设置

    Table  3.   Setting of the ablation study

    方法 基于海陆分割掩模的
    逐像素匹配
    结合海岸线采样点的
    分段线性变换
    GPU加速
    T0(本文算法)
    T1 ×
    T2 ×
    T3 ×
    下载: 导出CSV

    表  4  消融实验对比结果,包括定位误差(m)和平均处理时间(s)

    Table  4.   The comparison results of ablation study, including positioning error (m) and average processing time (s)

    测试区域 A1 A2 B C D1 D2 平均处理时间(s)
    T0 1.82 2.98 3.65 5.50 2.81 2.45 17.3
    T1 2.28 4.14 5.29 8.32 4.67 3.71 205.6
    T2 2.24 3.71 7.31 5.63 3.95 3.38 16.9
    T3 1.89 3.18 4.42 5.58 2.82 3.02 158.8
    下载: 导出CSV

    表  5  开源海岸线矢量与海陆分割的对比结果,包括定位误差(m)、平均处理时间(s)和采样点数量(个)

    Table  5.   The comparison results between open-source coastline vectors and land-sea segmentation, including positioning error (m), average processing time (s), and the number of sampling points (count)

    测试区域 定位误差(m) 平均处理时间(s) 采样点数量(个)
    开源海岸线矢量 海陆分割 开源海岸线矢量 海陆分割 开源海岸线矢量 海陆分割
    A1 1.82 1.92 14.2 22.2 269 1451
    A2 2.98 3.15 12.3 18.4 269 1451
    B 3.65 4.67 15.0 20.25 783 1253
    C 5.50 4.53 24.1 51.4 1119 3464
    D1 2.81 3.28 15.5 20.91 157 824
    D2 2.45 2.69 16.8 21.49 157 824
    下载: 导出CSV
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  • 收稿日期:  2024-02-03
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