基于超像素分割与多信息融合的叠掩和阴影区域检测法

doi:10.11947/j.AGCS.2022.20220111

测绘学报 ›› 2022, Vol. 51 ›› Issue (12): 2517-2530.doi: 10.11947/j.AGCS.2022.20220111

• 天绘二号卫星系列专栏 • 上一篇下一篇

基于超像素分割与多信息融合的叠掩和阴影区域检测法

刘鹏¹, 李真芳¹, 楼良盛^2,3, 杨伟明¹, 王震¹

1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西西安 710071;
2. 地理空间信息国家重点实验室, 陕西西安 710054;
3. 西安测绘研究所, 陕西西安 710054

收稿日期:2022-02-22 修回日期:2022-10-17 发布日期:2023-01-12
通讯作者: 李真芳 E-mail:lzf@xidian.edu.cn
作者简介:刘鹏(1995-),男,硕士,助理研究员,研究方向为SAR/InSAR数据处理。E-mail:lp18392965216@163.com
基金资助:
国家自然科学基金(62031005)

Layover and shadow regions detection based on superpixel segmentation and multi-information fusion

LIU Peng¹, LI Zhenfang¹, LOU Liangsheng^2,3, YANG Weiming¹, WANG Zhen¹

1. National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China;
2. State Key Laboratory of Geo-information Engineering, Xi'an 710054, China;
3. Xi'an Research Institute of Surveying and Mapping, Xi'an 710054, China

Received:2022-02-22 Revised:2022-10-17 Published:2023-01-12
Supported by:
The National Natural Science Foundation of China (No.62031005)

摘要/Abstract

摘要： InSAR信号处理中,叠掩和阴影区域严重破坏了InSAR相位图的连续性,导致高程反演出现错误。本文提出一种基于多信息融合的超像素检测算法,以弥补传统的基于幅度和相干系数阈值检测、恒虚警检测和局部频率检测等逐像素检测方法的不足。由于缺少真实场景的数字高程模型,导致无法验证所提算法在实际应用中的准确性,因此本文提出了基于先进积分方程近似模型的频域回波模拟技术,用于模拟给定场景的SAR回波数据以验证本文算法。仿真数据和TH-2数据试验表明,本文算法能够区分SAR图像中98%以上的叠掩区和阴影区。最后,通过将检测出的叠掩和阴影区域在相位解缠过程中进行掩膜,进一步提高了相位解缠速度和DEM产品精度。

关键词: 天绘二号, 叠掩, 阴影, 简单线性迭代聚类, 快速回波仿真

Abstract: In InSAR signal processing, the continuity of InSAR phase maps is seriously destroyed by layover and shadow regions which results in errors in elevation inversion. In this paper, a multi-information fusion-based superpiexl detection algorithm is proposed to make up for the shortcomings of traditional pixel-by-pixel detection methods based on amplitude and coherence coefficient threshold detection, constant false alarm(CFAR) detection and local frequency detection. Due to the lack of digital elevation model of scene, the accuracy verification of the proposed algorithm in practical applications become impossible. Thus, a frequency domain echo simulation technique is proposed. The proposed algorithm is verified based on an advanced integral equation approximation model(AIEM) for simulating SAR echo data. Simulation data and TH-2 data experiments show that the algorithm can distinguish more than 98% of layover and shadow regions in SAR images. Finally, the DEM products precision and the operation efficiency of phase unwrapping are improved significantly by masking layover and shadow regions during the phase unwrapping process.

Key words: TH-2, layover, shadow, simple linear iterative clustering(SLIC), fast echo simulation

中图分类号:

P236

刘鹏, 李真芳, 楼良盛, 杨伟明, 王震. 基于超像素分割与多信息融合的叠掩和阴影区域检测法[J]. 测绘学报, 2022, 51(12): 2517-2530.

LIU Peng, LI Zhenfang, LOU Liangsheng, YANG Weiming, WANG Zhen. Layover and shadow regions detection based on superpixel segmentation and multi-information fusion[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(12): 2517-2530.

参考文献

[1] DAI Keren, RAN Peilian, LI Zhenhong, et al. Land subsidence in Xiong'an new area, China revealed by InSAR observations[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(1):70-76.
[2] LIU Guang, ZBIGNIEW P, STEFANO S, et al. Land surface displacement geohazards monitoring using multi-temporal InSAR techniques[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(1):77-87.
[3] TANG Xinming, LI Tao, GAO Xiaoming, et al. Research on key technologies of precise InSAR surveying and mapping applications using automatic SAR imaging[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(1):72.
[4] 张勤, 黄观文, 杨成生. 地质灾害监测预警中的精密空间对地观测技术[J]. 测绘学报, 2017, 46(10):1300-1307.DOI:10.11947/j.AGCS.2017.20170453. ZHANG Qin, HUANG Guanwen, YANG Chengsheng. Precision space observation technique for geological hazard monitoring and early warning[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10):1300-1307.DOI:10.11947/j.AGCS.2017.20170453.
[5] SOERGEL U, SCHULZ K, THOENNESSEN U. Enhancement of interferometric SAR data using segmented intensity information in urban areas[C]//Proceedings of the IEEE 2000 International Geoscience and Remote Sensing Symposium(IGARSS). Honolulu, HI, USA. IEEE, 2000:3216-3218.
[6] 王健, 向茂生, 李绍恩. 一种基于InSAR相干系数的SAR阴影提取方法[J]. 武汉大学学报(信息科学版), 2005, 30(12):1063-1066. WANG Jian, XIANG Maosheng, LI Shaoen. A method for extracting the SAR shadow from InSAR coherence[J]. Geomatics and Information Science of Wuhan University, 2005, 30(12):1063-1066.
[7] 陈绍武, 王卫星, 金文标. 基于边缘特征和模糊理论的阴影检测[J]. 微计算机信息, 2007, 23(3):294-296. CHEN Shaowu, WANG Weixing, JIN Wenbiao. Shadow detection based on edge feature and fuzzy theory[J]. Microcomputer Information, 2007, 23(3):294-296.
[8] DU Xiangyu, YANG Qi, CAI Bin, et al. A new method on shadow and layover detection of InSAR[C]//Proceedings of the 6th Asia-Pacific Conference on Antennas and Propagation (APCAP). Xi'an, China:IEEE, 2017:1-3.
[9] WANG Siyuan, XU Huaping, YANG Bo, et al. Improved InSAR layover and shadow detection using multi-feature[C]//Proceedings of 2020 IEEE International Geoscience and Remote Sensing Symposium(IGARSS). Waikoloa, HI, USA. IEEE, 2020:28-31.
[10] 任云. InSAR叠掩与阴影检测技术[D]. 长沙:国防科学技术大学, 2013. REN Yun. Research on layover and shadow detecting in InSAR[D].Changsha:National University of Defense Technology, 2013.
[11] LIU Mingyu, TUZEL O, RAMALINGAM S, et al. Entropy rate superpixel segmentation[C]//Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. Colorado Springs, CO, USA:IEEE,2011:2097-2104.
[12] ZHANG Yuhang, HARTLEY R, MASHFORD J, et al. Superpixels via pseudo-boolean optimization[C]//Proceedings of the 2011 International Conference on Computer Vision. New York:ACM, 2011:1387-1394.
[13] FELZENSZWALB P F, HUTTENLOCHER D P. Efficient graph-based image segmentation[J].International Journal of Computer Vision, 2004, 59(2):167-181.
[14] ACHANTA R, SHAJI A, SMITH K, et al. SLIC super pixels[R]. Lausanne:Ecole Polytechnique Federal de Lausanne(EPFL),2010.
[15] ZHU Song, CAO Danhua, JIANG Shixiong, et al. Fast superpixel segmentation by iterative edge refinement[J]. Electronics Letters, 2015, 51(3):230-232.
[16] JOHNSON B, XIE Zhixiao. Unsupervised image segmentation evaluation and refinement using a multi-scale approach[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(4):473-483.
[17] VINCENT L, SOILLE P. Watersheds in digital spaces:an efficient algorithm based on immersion simulations[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(6):583-598.
[18] ACHANTA R, SHAJI A, SMITH K, et al. SLIC superpixels compared to state-of-the-art superpixel methods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11):2274-2282.
[19] 黄世奇, 刘代志. SAR图像斑点噪声抑制方法与应用研究[J]. 测绘学报, 2006, 35(3):245-250. HUANG Shiqi, LIU Daizhi. Research on method and application of speckle noise reduction of SAR image[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(3):245-250.
[20] HU Zhongwen, LI Qingquan, ZOU Qin, et al. A bilevel scale-sets model for hierarchical representation of large remote sensing images[J].IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12):7366-7377.
[21] ZOU Huanxin, QIN Xianxiang, KANG Hongyan, et al. A PDF-based SLIC superpixel algorithm for SAR images[C]//Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium. Beijing, China:IEEE,2016:6823-6826.
[22] ZHANG Lamei, HAN Cuijuan, CHENG Yan. Improved SLIC superpixel generation algorithm and its application in polarimetric SAR images classification[C]//Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium(IGARSS). Fort Worth, TX, U.S.:IEEE,2017:4578-4581.
[23] YIN Junjun, WANG Tao, DU Yanlei, et al. SLIC superpixel segmentation for polarimetric SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60:1-17.
[24] ZENG Jiangyuan, CHEN Kunshan, XU Peng, et al. Rough soil surface scattering and emission modeling:a comprehensive reappraisal of the AIEM model by using numerical and experimental data[C]//Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium. Fort Worth, TX, USA:IEEE,2017:1441-1444.
[25] WU T D, CHEN K S, SHI Jiancheng, et al. A transition model for the reflection coefficient in surface scattering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(9):2040-2050.
[26] FRANCESCHETTI G, MIGLIACCIO M. SARAS:a synthetic aperture radar (SAR) raw signal simulator[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(1):110-123.
[27] 楼良盛,刘志铭,张昊,等.天绘二号卫星关键技术[J].测绘学报,2022,51(12):2403-2416.DOI:10.11947/j.AGCS.2022.20210567. LOU Liangsheng, LIU Zhiming, ZHANG Hao, et al. Key technology of TH-2 satellite system[J]. Acta Geodaetica et Cartographica Sinica, 2022,51(12):2403-2416.DOI:10.11947/j.AGCS.2022.20210567.
[28] 楼良盛, 刘志铭, 张昊, 等. 天绘二号卫星工程设计与实现[J]. 测绘学报, 2020, 49(10):1252-1264. DOI:10.11947/j.AGCS.2020.20200175. LOU Liangsheng, LIU Zhiming, ZHANG Hao, et al. TH-2 satellite engineering design and implementation[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(10):1252-1264.DOI:10.11947/j.AGCS.2020.20200175.
[29] 仇晓兰, 丁赤飚, 胡东辉. 双站SAR成像处理技术[M]. 北京:科学出版社, 2010. QIU Xiaolan, DING Chibiao, HU Donghui. Bistatic SAR imaging processing technology[M]. Beijing:Science Press, 2010.

基于超像素分割与多信息融合的叠掩和阴影区域检测法

Layover and shadow regions detection based on superpixel segmentation and multi-information fusion

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	楼良盛, 刘志铭, 张昊, 钱方明, 张笑微. 天绘二号卫星关键技术[J]. 测绘学报, 2022, 51(12): 2403-2416.
[2]	钱方明, 陈刚, 楼良盛, 刘薇, 张昊, 孟欣. 天绘二号卫星两种基线定标模型比较分析[J]. 测绘学报, 2022, 51(12): 2425-2432.
[3]	陈力, 张德新, 陈筠力, 邵晓巍. 分布式InSAR卫星系统编队指标体系研究[J]. 测绘学报, 2022, 51(12): 2433-2439.
[4]	李楠, 丛琳, 陈重华, 赵迪, 侯雨生, 陈熙之. 多约束条件分布式InSAR编队构形工程优化方法[J]. 测绘学报, 2022, 51(12): 2440-2447.
[5]	陈重华, 李楠, 完备, 杜耀珂, 王文妍, 孙英梅. InSAR卫星编队构形保持控制方法[J]. 测绘学报, 2022, 51(12): 2448-2454.
[6]	黄艳, 张笑微, 丛琳, 董小环. 天绘二号时间同步误差分析与评估验证[J]. 测绘学报, 2022, 51(12): 2455-2461.
[7]	王赛, 孟欣, 楼良盛, 陈刚, 钱方明, 刘志铭. 天绘二号卫星单幅SAR影像定位性能评估[J]. 测绘学报, 2022, 51(12): 2501-2507.
[8]	王伟, 李春艳, 孙韬, 杨戬峰, 喻夏琼, 务宇宽. 天绘二号01组SAR图像质量评价[J]. 测绘学报, 2022, 51(12): 2508-2516.
[9]	邵凯, 张厚喆, 秦显平, 黄志勇, 易彬, 谷德峰. 分布式InSAR编队卫星精密绝对和相对轨道确定[J]. 测绘学报, 2021, 50(5): 580-588.
[10]	楼良盛, 刘志铭, 张昊, 钱方明, 黄艳. 天绘二号卫星工程设计与实现[J]. 测绘学报, 2020, 49(10): 1252-1264.
[11]	岳照溪, 张永军, 段延松, 余磊. DEM辅助的卫星光学遥感影像山体阴影检测与地形辐射校正[J]. 测绘学报, 2018, 47(1): 113-122.
[12]	田峰, 李虎. 联合星载光学与SAR图像的城市大面积建筑物高度快速提取[J]. 测绘学报, 2017, 46(7): 891-899.
[13]	曹天扬, 申莉. 应用光照模型的交通车辆识别定位的高分辨率遥感方法[J]. 测绘学报, 2015, 44(1): 39-45.
[14]	都伟冰, 李均力, 包安明, 王宝山, 王双亭. 高山冰川多时相多角度遥感信息提取方法[J]. 测绘学报, 2015, 44(1): 59-66.
[15]	杨乃,孔凡秋,杨鸿海,张百灵. 基于空间认知的三维地图光影模型[J]. 测绘学报, 2012, 41(2): 302-308.