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

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

向俞明^{1, 2, 3, ,},
滕飞^{1, 2},
王林徽^{1, 2, 3},
焦念刚^{1, 2},
王峰^{1, 2},
尤红建^{1, 2, 3}

1.
中国科学院空天信息创新研究院北京 100094
2.
中国科学院空间信息处理与应用系统技术重点实验室北京 100190
3.
中国科学院大学电子电气和通信工程学院北京 100049

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
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出版历程
- 收稿日期: 2024-02-03
- 修回日期: 2024-03-27
- 网络出版日期: 2024-04-24
- 刊出日期: 2024-08-28

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

XIANG Yuming^{1, 2, 3
, ,},
TENG Fei^{1, 2},
WANG Linhui^{1, 2, 3},
JIAO Niangang^{1, 2},
WANG Feng^{1, 2},
YOU Hongjian^{1, 2, 3}

1.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2.
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China
3.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Funds: Key Research Program of Frontier Sciences, Chinese Academy of Sciences (ZDBS-LY-JSC036), The National Natural Science Foundation of China (61901439)

More Information

Corresponding author: XIANG Yuming, xiangym@aircas.ac.cn

摘要

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。
- 合成孔径雷达 /
- 遥感影像配准 /
- 正射校正 /
- 光学SAR配准 /
- 海岛区域 /
- 海岸线矢量
Abstract: With the successive launch of high-resolution Synthetic Aperture Radar (SAR) satellites, conducting all-weather, all-time high-precision observation of island regions with variable weather conditions has become feasible. As a key preprocessing step in various remote sensing applications, orthorectification relies on high-precision control points to correct the geometric positioning errors of SAR images. However, obtaining artificial control points that meet SAR correction requirements in island areas is costly and risky. To address this challenge, this study first proposes a rapid registration algorithm for optical and SAR heterogeneous images, and then automatically extracts control points based on an optical reference base map, achieving orthorectification of SAR images in island regions. The proposed registration algorithm consists of two stages: constructing dense common features of heterogeneous images; performing pixel-by-pixel matching on the down-sampled features, to avoid the issue of low repeatability of feature points in heterogeneous images. To reduce the matching complexity, a land sea segmentation mask is introduced to limit the search range. Subsequently, local fine matching is applied to the preliminary matched points to reduce inaccuracies introduced by down-sampling. Meanwhile, uniformly sampled coastline points are introduced to enhance the uniformity of the matching results, and orthorectified images are generated through a piecewise linear transformation model, ensuring the overall correction accuracy in sparse island areas. This algorithm performs excellently on the high-resolution SAR images of multiple scenes in island regions, with an average positioning error of 3.2 m and a complete scene correction time of only 17.3 s, both these values are superior to various existing advanced heterogeneous registration and correction algorithms, demonstrating the great potential of the proposed algorithm in engineering applications.
- Synthetic Aperture Radar (SAR) /
- Remote sensing image registration /
- Orthorectification /
- Optical and SAR image registration /
- Island /
- Coastline shapefile

HTML全文

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)

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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	41.2	C	0.56/0.36	15616×29344
A2	高分三号	滑动聚束	21.4	C	0.56/0.31	8635×33560
B	高分三号	滑动聚束	39.3	C	0.56/0.34	13660×32208
C	高分三号	滑动聚束	29.7	C	0.56/0.33	10946×32032
D1	海丝一号	滑动聚束	28.0	C	0.31/0.17	9188×45875
D2	海丝一号	滑动聚束	28.8	C	0.31/0.32	12748×22937

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)

方法	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)
测试区域	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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