SAR图像海岸线检测的区域距离正则化几何主动轮廓模型

姜大伟; 范剑超; 黄凤荣

doi:10.11947/j.AGCS.2016.20160039

测绘学报 >

2016 , Vol. 45 >Issue 9: 1096 - 1103

DOI: https://doi.org/10.11947/j.AGCS.2016.20160039

摄影测量学与遥感

SAR图像海岸线检测的区域距离正则化几何主动轮廓模型

姜大伟 ,
范剑超 ,
黄凤荣

展开

1. 辽宁师范大学城市与环境学院, 辽宁大连 116029;
2. 国家海洋环境监测中心海域资源环境动态监管中心, 辽宁大连 116023

姜大伟(1991-),男,硕士生,研究方向为海洋遥感SAR图像处理、海域使用动态监测.E-mail:18840817436@163.com

收稿日期: 2016-02-24

修回日期: 2016-06-16

网络出版日期: 2016-09-29

基金资助

国家自然科学基金（61273307）；中国博士后面上基金（2014M551082）；高分辨率对地观测系统重大专项（41-Y30B12-9001-14/16）

收起

SAR Image Coastline Detection Based on Regional Distance Regularized Geometric Active Contour Models

JIANG Dawei ,
FAN Jianchao ,
HUANG Fengrong

Expand

1. School of Urban Environment, Liaoning Normal University, Dalian 116029, China;
2. Marine Resources and Environment Monitoring Center, National Marine Environmental Monitoring Center, Dalian 116023, China

Received date: 2016-02-24

Revised date: 2016-06-16

Online published: 2016-09-29

Supported by

The National Natural Science Foundation of China (No.61273307);The China Postdoctoral Science Foundation (No.2014M551082);High Resolution Special Research (No.41-Y30B12-9001-14/16).

Fold

摘要

合成孔径雷达（SAR）卫星遥感图像可以极大地提高全国海岸线覆盖频率，然而受到海洋波浪所引起的随机海水表面粗糙度的影响，海岸目标与海水背景边界易混淆不清，因此本文提出了基于区域距离正则化几何主动轮廓模型（RDRGAC），引入距离正则项，解决重复初始化水平集函数为符号距离函数的问题，提高了算法收敛速度。此外，将区域面积项系数与SAR图像等效视数（ENL）建立非线性拟合关系，实现RDRGAC模型根据不同SAR遥感图像的自适应调整，改善海岸线自动提取精度。通过河北省北戴河和大连市金州湾SAR数据海岸线提取对比试验，验证了所提方法的有效性。

关键词： 相干斑噪声; 合成孔径雷达; 非线性拟合; 几何主动轮廓模型; 等效视数

本文引用格式

姜大伟 , 范剑超 , 黄凤荣 . SAR图像海岸线检测的区域距离正则化几何主动轮廓模型[J]. 测绘学报, 2016 , 45(9) : 1096 -1103 . DOI: 10.11947/j.AGCS.2016.20160039

Abstract

Synthetic aperture radar (SAR) satellite remote sensing images can greatly increase the frequency of the coastline coverage all over the country. However, due to the influence of the random sea surface roughness caused by waves, it's a challenge to distinguish the coastline and sea boundary. To solve this problem, this paper proposes regional distance regularized geometric active contour models (RDRGAC), in which the distance regularized term is introduced to avoid periodically initializing the degraded function with a signed distance function, accelerating the speed of convergence. Besides, it establishes the nonlinear regression relationship between the regional term parameters and equivalent number of looks (ENL) in SAR images, leading to the adaptive setting of RDRGAC model with different SAR images, which could improve the accuracy of coastline automatic detection in return. In the experiments, SAR images in Beidaihe and Dalian Jinzhou Bay respectively are adopted to detect the coastline, verifying the effective of the proposed method.

Key words： speckle noise; synthetic aperture radar; nonlinear regression relationship; geometric active contour model; equivalent number of looks

参考文献

[1] 马小峰, 赵冬至, 张丰收, 等. 海岸线卫星遥感提取方法研究进展[J]. 遥感技术与应用, 2007, 22(4): 575-580. MA Xiaofeng, ZHAO Dongzhi, ZHANG Fengshou, et al. An Overview of Means of Withdrawing Coastline by Remote Sensing[J]. Remote Sensing Technology and Application, 2007, 22(4): 575-580.
[2] 严海兵, 李秉柏, 陈敏东. 遥感技术提取海岸线的研究进展[J]. 地域研究与开发, 2009, 28(1): 101-105. YAN Haibing, LI Bingbai, CHEN Mindong. Progress of Researches in Coastline Extraction Based on RS Technique[J]. Areal Research and Development, 2009, 28(1): 101-105.
[3] 李雨谦, 皮亦鸣, 王金峰. 基于水平集的SAR图像与光学图像的配准[J]. 测绘学报, 2010, 39(3): 276-282. LI Yuqian, PI Yiming, WANG Jinfeng. The Registration between SAR and Optical Image Based on Level Set[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(3): 276-282.
[4] 周奇年, 王廷波, 李文书. 区域信息和水平集方法的图像分割[J]. 中国图象图形学报, 2011, 16(11): 2002-2008. ZHOU Qinian, WANG Tingbo, LI Wenshu. Image Segmentation Based on Region and Level Set Method[J]. Journal of Image and Graphics, 2011, 16(11): 2002-2008.
[5] 胡倩, 张丰, 刘仁义, 等. 基于梯度矢量流和主动轮廓模型的海陆边界提取[J]. 浙江大学学报(理学版), 2013, 40(6): 698-704. HU Qian, ZHANG Feng, LIU Renyi, et al. Land Sea Boundary Extraction Based on Gradient Vector Flow and Active Contour Model[J]. Journal of Zhejiang University (Science Edition), 2013, 40(6): 698-704.
[6] 孙阳光, 蔡超, 周成平, 等. R-Snake: 一种基于边缘与区域信息的图像主动轮廓模型提取[J]. 电子学报, 2009, 37(8): 1810-1815. SUN Yangguang, CAI Chao, ZHOU Chengping, et al. R-Snake: A Snake Model Using Both Boundary and Region Information[J]. Acta Electronica Sinica, 2009, 37(8): 1810-1815.
[7] SUN Guangcai, XING Mengdao, XIA Xianggen, et al. Multichannel Full-aperture Azimuth Processing for Beam Steering SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(9): 4761-4778.
[8] 刘鹏程. 基于水平集理论的海岸线轮廓特征提取[J]. 国土资源遥感, 2015, 27(2): 75-79. LIU Pengcheng. Feature Extraction of Coastline Contour Based on Level Set Theory[J]. Remote Sensing for Land & Resources, 2015, 27(2): 75-79.
[9] YANG Xi, GAO Xinbo, TAO Dacehng, et al. An Efficient MRF Embedded Level Set Method for Image Segmentation[J]. IEEE Transactions on Image Processing, 2015, 24(1): 9-21.
[10] 欧阳越, 种劲松. SAR图像海岸线检测算法综述[J]. 国土资源遥感, 2006, 18(2): 1-3. OUYANG Yue, ZHONG Jinsong. A Review of Coastline Detection on SAR Imagery[J]. Remote Sensing for Land & Resources, 2006, 18(2): 1-3.
[11] 涂松, 李禹, 粟毅. 基于主动轮廓模型的SAR图像分割方法综述[J]. 系统工程与电子技术, 2015, 37(8): 1754-1766. TU Song, LI Yu, SU Yi. Overview of SAR Image Segmentation Based on Active Contour Model[J]. Systems Engineering and Electronics, 2015, 37(8): 1754-1766.
[12] LI Chunming, XU Chenyang, GUI Changfeng, et al. Distance Regularized Level Set Evolution and Its Application to Image Segmentation[J]. IEEE Transactions on Image Processing, 2010, 19(12): 3243-3254.
[13] COLGAN T J, HAGNESS S C, VAN VEEN B D. A 3-D Level Set Method for Microwave Breast Imaging[J]. IEEE Transactions on Biomedical Engineering, 2015, 62(10): 2526-2534.
[14] 任继军, 何明一. 基于粒子群优化算法的改进Snake模型的图像分割方法[J]. 中国图像图形学报, 2008, 13(9): 1727-1732. REN Jijun, HE Mingyi. Image Segmentation Using Improved Snake Model Based on Particle Swarm Optimization[J]. Journal of Image and Graphics, 2008, 13(9): 1727-1732.
[15] 东野长磊, 郑永果, 苏杰. 基于Chan-Vese模型的SAR图像分割[J]. 数据采集与处理, 2012, 27(2): 151-155. DONGYE Changlei, ZHENG Yongguo, SU Jie. SAR Image Segmentation Based on Chan-Vese Model[J]. Journal of Data Acquisition & Processing, 2012, 27(2): 151-155.
[16] 王相海, 李明. 双重轮廓演化曲线的图像分割水平集模型[J]. 中国图象图形学报, 2014, 19(3): 373-380. WANG Xianghai, LI Ming. Level Set Model for Image Segmentation Based on Dual Contour Evolutional Curve[J]. Journal of Image and Graphics, 2014, 19(3): 373-380.
[17] 黄魁华, 张军. 局部统计活动轮廓模型的SAR图像海岸线检测[J]. 遥感学报, 2011, 15(4): 737-749. HUANG Kuihua, ZHANG Jun. A Coastline Detection Method Using SAR Images Based on the Local Statistical Active Contour Model[J]. Journal of Remote Sensing, 2011, 15(4): 737-749.
[18] 李传龙, 李颖, 兰国新. 一种新的窄带快速区域水平集C-V模型图像分割方法[J]. 计算机科学, 2011, 38(12): 17-19, 35. LI Chuanlong, LI Ying, LAN Guoxin. New Method of the Fast Narrow Brand C-V Level Set Model for Image Segmentation[J]. Computer Science, 2011, 38(12): 17-19, 35.
[19] 吴良斌. SAR图像处理与目标识别[M]. 北京: 航空工业出版社, 2013: 21-22. WU Liangbin. SAR Image Processing and Target Recognition[M]. Beijing: Aviation Industry Press, 2013: 21-22.
[20] 崔瑞, 薛磊, 汪波. 基于等效视数的ISAR干扰效果评估方法[J]. 系统工程与电子技术, 2008, 30(5): 887-888. CUI Rui, XUE Lei, WANG Bo. Evaluation Method of Jamming Effect on ISAR Based on Equivalent Number of Looks[J]. Systems Engineering and Electronics, 2008, 30(5): 887-888.
[21] 王晓军, 孙洪. SAR图像相干斑滤波性能评估模型[J]. 雷达科学与技术, 2008, 6(1): 29-34, 38. WANG Xiaojun, SUN Hong. Measurement Model and Performance Evaluation for Speckle Filter of SAR Images[J]. Radar Science and Technology, 2008, 6(1): 29-34, 38.

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献