GVF Snake与显著特征相结合的高分辨率遥感图像道路提取

doi:10.11947/j.AGCS.2017.20170393

测绘学报 ›› 2017, Vol. 46 ›› Issue (12): 1978-1985.doi: 10.11947/j.AGCS.2017.20170393

GVF Snake与显著特征相结合的高分辨率遥感图像道路提取

王峰萍, 王卫星, 薛柏玉, 曹霆, 高婷

长安大学信息工程学院, 陕西西安 710064

收稿日期:2017-07-14 修回日期:2017-09-07 出版日期:2017-12-20 发布日期:2017-12-28
通讯作者: 王卫星 E-mail:znn525d@qq.com
作者简介:王峰萍(1987-),女,博士生,研究方向为图像处理、模式识别等。E-mail:tiffany0209@126.com
基金资助:
国家自然科学基金（41372330）；中央高校基本科研业务费专项资金（310824165003）

Road Extraction from High-spatial-resolution Remote Sensing Image by Combining GVF Snake with Salient Features

WANG Fengping, WANG Weixing, XUE Baiyu, CAO Ting, GAO Ting

School of Information Engineering, Chang'an University, Xi'an 710064, China

Received:2017-07-14 Revised:2017-09-07 Online:2017-12-20 Published:2017-12-28
Supported by:
The National Natural Science Foundation of China (No. 41372330) The Fundamental Research Funds for the Central Universities (No. 310824165003)

摘要/Abstract

摘要： 高分辨率遥感图像中的道路信息，对地理信息系统数据库的更新具有重要的意义。本文通过分析道路在遥感图像中所呈现的特性，提出了一种基于显著特征和GVF Snake的高分辨率遥感图像道路提取方法。该方法根据视觉认知理论将道路的几何特性和辐射特征作为显著特性。首先，通过融合颜色对比度和空间统计特征计算显著性图，并以输出的显著图的最大值作为GVF Snake的初始种子点；再利用区域生长法求出道路的初始边界，通过梯度矢量流模型的迭代求解，并最小化能量函数，实现道路信息的自动提取。试验结果表明，本文所提出的方法提高了不仅可以提高计算效率，还具有较好的检测精度。

关键词: 遥感图像, 道路提取, 显著特征, GVF Snake

Abstract: The road information in the high-spatial-resolution remote sensing image is of great significance for updating the GIS database. Through analyzing the road features shown in the remote sensing image, this paper presents a road detection method based on salient features and gradient vector flow (GVF) Snake. According to the visual cognition theory, the road geometric and radiation features are viewed as salient features in this paper. First, the saliency map is calculated by fusing the color-based and structure-based contrasts, the maximum saliency value is regarded as the seeds of the GVF Snake. Then, a region-growing algorithm is applied to compute the initial boundaries, the energy function of the GVF Snake is minimized by iterative solution of the gradient vector flow model to get the final road information.Experimental results show that the proposed method could enhance the computational efficiency and has good detection accuracy.

Key words: remote sensing image, road extraction, salient feature, GVF Snake

中图分类号:

P237

王峰萍, 王卫星, 薛柏玉, 曹霆, 高婷. GVF Snake与显著特征相结合的高分辨率遥感图像道路提取[J]. 测绘学报, 2017, 46(12): 1978-1985.

WANG Fengping, WANG Weixing, XUE Baiyu, CAO Ting, GAO Ting. Road Extraction from High-spatial-resolution Remote Sensing Image by Combining GVF Snake with Salient Features[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(12): 1978-1985.

参考文献

[1] 荣岳成.大数据量遥感分类图像的动态矢量化算法[J].测绘学报,2012,41(6):898-903. RONG Yuecheng.A Dynamic Algorithm of Vectorization for Large Classified Remote Sensing Image[J].Acta Geodaetica et Cartographica Sinica,2012,41(6):898-903.
[2] WANG Weixing,YANG Nan,ZHANG Yi,et al.A Review of Road Extraction from Remote Sensing Images[J].Journal of Traffic and Transportation Engineering,2016,3(3):271-282.
[3] DAS S,MIRNALINEE T T,VARGHESE K.Use of Salient Features for the Design of a Multistage Framework to Extract Roads from High-resolution Multispectral Satellite Images[J].IEEE Transactions on Geoscience and Remote Sensing,2011,49(10):3906-3931.
[4] XU Chengyang,PRINCE J L.Gradient Vector Flow:A New External Force for Snakes[C]//Proceedings of 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San Juan,Puerto Rico:IEEE,1997:66-71.
[5] 唐伟,赵书河.基于GVF和Snake模型的高分辨率遥感图像四元数空间道路提取[J].遥感学报,2011,15(5):1040-1052. TANG Wei,ZHAO Shuhe.Road Extraction in Quaternion Space from High Spatial Resolution Remotely Sensed Images Basing on GVF Snake Model[J].Journal of Remote Sensing,2011,15(5):1040-1052.
[6] 符喜优,张风丽,王国军,等.基于模糊连接度的高分辨率SAR图像道路自动提取[J].计算机应用,2015,35(2):523-527. FU Xiyou,ZHANG Fengli,WANG Guojun,et al.Automatic Road Extraction from High Resolution SAR Images Based on Fuzzy Connectedness[J].Journal of Computer Applications,2015,35(2):523-527.
[7] DENG Xinping,HE Chu,SUN Hong.An Improved GVF Snake Model and Its Application to Linear Feature Extraction from SAR Images[C]//Proceedings of the 10th International Conference on Signal Processing (ICSP).Beijing,China:IEEE,2010:2063-2066.
[8] KUSUMANDARI D E,ARISMUNANDAR,REDHYKA G G.The Comparison of GVF Snake Active Contour Method and Ellipse Fit in Optic Disc Detection for Glaucoma Diagnosis[C]//Proceedings of 2015 International Conference on Automation,Cognitive Science,Optics,Micro Electro-Mechanical System,and Information Technology (ICACOMIT).Bandung,Indonesia:IEEE,2015:123-126.
[9] 毕晓君,肖婧.差分进化算法GVF Snake模型在PET图像分割中的应用[J].中国图象图形学报,2011,16(3):382-388. BI Xiaojun,XIAO Jing.Application of DE Algorithm and Improved GVF Snake Model in Segmentation of PET Image[J].Journal of Image and Graphics,2011,16(3):382-388.
[10] 姜霞霞,李宗民,匡振中,等.融合双层信息的显著性检测[J].中国图象图形学报,2015,20(3):340-348. JIANG Xiaxia,LI Zongmin,KUANG Zhenzhong,et al.Image Saliency Detection Based on Two-layer Information Fusion[J].Journal of Image and Graphics,2015,20(3):340-348.
[11] 魏龙生,罗大鹏.基于视觉注意机制的遥感图像显著性目标检测[J].计算机工程与应用,2014,50(19):11-15. WEI Longsheng,LUO Dapeng.Saliency Remote Sensing Image Object Detection Model Based on Visual Attention Mechanism[J].Computer Engineering and Applications,2014,50(19):11-15.
[12] CHENG Mingming,ZHANG Guoxin,MITRA N J,et al.Global Contrast Based Salient Region Detection[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Colorado Springs,CO:IEEE,2011:409-416.
[13] 唐勇,杨林,段亮亮.基于图像单元对比度与统计特性的显著性检测[J].自动化学报,2013,39(10):1632-1641. TANG Yong,YANG Lin,DUAN Liangliang.Image Cell Based Saliency Detection VIA Color Contrast and Distribution[J].Acta Automatica Sinica,2013,39(10):1632-1641.
[14] 何小飞,邹峥嵘,陶超,等.联合显著性和多层卷积神经网络的高分影像场景分类[J].测绘学报,2016,45(9):1073-1080.DOI:10.11947/j.AGCS.2016.20150612. HE Xiaofei,ZOU Zhengrong,TAO Chao,et al.Combined Saliency with Multi-convolutional Neural Network for High Resolution Remote Sensing Scene Classification[J].Acta Geodaetica et Cartographica Sinica,2016,45(9):1073-1080.DOI:10.11947/j.AGCS.2016.20150612.
[15] 黄志勇,何发智,蔡贤涛,等.一种随机的视觉显著性检测算法[J].中国科学:信息科学,2011,41(7):863-874. HUANG Zhiyong,HE Fazhi,CAI Xiantao,et al.Efficient Random Saliency Map Detection[J].Science China:Information Sciences,2011,41(7):863-874.
[16] SHI Keyang,WANG Keze,LU Jiangbo,et al.PISA:Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors[C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition.Portland,OR:IEEE,2013:2115-2122.
[17] GUAN Tao,ZHOU Dongxiang,LIU Yunhui.Accurate Segmentation of Partially Overlapping Cervical Cells Based on Dynamic Sparse Contour Searching and GVF Snake Model[J].IEEE Journal of Biomedical and Health Informatics,2015,19(4):1494-1504.
[18] 朱述龙,孟伟灿,朱宝山.运用GVF Snake算法提取水域的不规则边界[J].遥感学报,2013,17(4):742-758. ZHU Shulong,MENG Weican,ZHU Baoshan.Irregular Water Boundary Extraction Using GVF Snake[J].Journal of Remote Sensing,2013,17(4):742-758.
[19] 孟伟灿,朱述龙,朱宝山,等.区域生长与GVF Snake模型相结合的水域边界提取[J].测绘科学技术学报,2011,28(4):262-265. MENG Weican,ZHU Shulong,ZHU Baoshan,et al.Water Area Boundary Extraction Based on GVF Snake Model and Region Growth[J].Journal of Geomatics Science and Technology,2011,28(4):262-265.
[20] ANAND A,TRIPATHY S S,KUMAR R S.An Improved Edge Detection Using Morphological Laplacian of Gaussian Operator[C]//Proceedings of the 2nd International Conference on Signal Processing and Integrated Networks.Noida,India:IEEE,2015:532-536.
[21] 周亚男,程熙,骆剑承,等.改进GVF的自动Snakes模型[J].中国图象图形学报,2012,17(2):256-262. ZHOU Yanan,CHENG Xi,LUO Jiancheng,et al.Automatic Snakes Model Based on Modified GVF[J].Journal of Image and Graphics,2012,17(2):256-262.
[22] VPLab,Downloads[EB/OL].(2016).http://www.cse.iitm.ac.in/~sdas/vplab/satellite.html.
[23] 曹云刚,王志盼,慎利,等.像元与对象特征融合的高分辨率遥感影像道路中心线提取[J].测绘学报,2016,45(10),1231-1240,1249.DOI:10.11947/j.AGCS.2016.20160158. CAO Yungang,WANG Zhipan,SHEN Li,et al.Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery[J].Acta Geodaetica et Cartographica Sinica,2016,45(10),1231-1240,1249.DOI:10.11947/j.AGCS.2016.20160158.
[24] LIU Junyi,SUI Haigang,TAO Mingming,et al.Road Extraction from SAR Imagery Based on an Improved Particle Filtering and Snake Model[J].International Journal of Remote Sensing,2013,34(22):8199-8214.
[25] 陈光,眭海刚,涂继辉,等.基于P-N学习的高分遥感影像道路半自动提取方法[J].武汉大学学报(信息科学版),2017,42(6):775-781. CHEN Guang,SUI Haigang,TU Jihui,et al.Semi-automatic Road Extraction Method from High Resolution Remote Sensing Images Based on P-N Learning[J].Geomatics and Information Science of Wuhan University,2017,42(6):775-781.

GVF Snake与显著特征相结合的高分辨率遥感图像道路提取

Road Extraction from High-spatial-resolution Remote Sensing Image by Combining GVF Snake with Salient Features

PDF

可视化

被引次数

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]	叶发茂, 孟祥龙, 董萌, 聂运菊, 葛芸, 陈晓勇. 遥感图像蚁群算法和加权图像到类距离检索法[J]. 测绘学报, 2021, 50(5): 612-620.
[2]	陆川伟, 孙群, 陈冰, 温伯威, 赵云鹏, 徐立. 车辆轨迹数据的道路学习提取法[J]. 测绘学报, 2020, 49(6): 692-702.
[3]	王舒洋, 慕晓冬, 贺浩, 杨东方, 马晨晖. 航拍图像跨数据域特征迁移道路提取方法[J]. 测绘学报, 2020, 49(5): 611-621.
[4]	周建伟, 吴一全. MRELBP特征、Franklin矩和SVM相结合的遥感图像建筑物识别方法[J]. 测绘学报, 2020, 49(3): 355-364.
[5]	方莉娜, 卢丽靖, 赵志远, 王昀昀, 陈崇成. 车载激光点云道路边界提取的Snake方法[J]. 测绘学报, 2020, 49(11): 1438-1450.
[6]	李雪, 张力, 王庆栋, 艾海滨. 多时相遥感影像语义分割色彩一致性对抗网络[J]. 测绘学报, 2020, 49(11): 1473-1484.
[7]	贺浩, 王仕成, 杨东方, 王舒洋, 刘星. 基于Encoder-Decoder网络的遥感影像道路提取方法[J]. 测绘学报, 2019, 48(3): 330-338.
[8]	赵生银, 安如, 朱美如. 联合像元-深度-对象特征的遥感图像城市变化检测[J]. 测绘学报, 2019, 48(11): 1452-1463.
[9]	姚群力, 胡显, 雷宏. 基于多尺度融合特征卷积神经网络的遥感图像飞机目标检测[J]. 测绘学报, 2019, 48(10): 1266-1274.
[10]	林文杰, 李玉, 赵泉华. 结合MST划分和RHMRF-FCM算法的高分辨率遥感图像分割[J]. 测绘学报, 2019, 48(1): 64-74.
[11]	连仁包, 王卫星, 李娟. 自适应圆形模板及显著图的高分辨遥感图像道路提取[J]. 测绘学报, 2018, 47(7): 950-958.
[12]	戴玉超, 张静, Fatih PORIKLI, 何明一. 深度残差网络的多光谱遥感图像显著目标检测[J]. 测绘学报, 2018, 47(6): 873-881.
[13]	胡根生, 周文利, 梁栋, 鲍文霞. 融合引导滤波和迁移学习的薄云图像中地物信息恢复算法[J]. 测绘学报, 2018, 47(3): 348-358.
[14]	许夙晖, 慕晓冬, 赵鹏, 马骥. 利用多尺度特征与深度网络对遥感影像进行场景分类[J]. 测绘学报, 2016, 45(7): 834-840.
[15]	曹帆之, 朱述龙, 朱宝山, 李润生, 孟伟灿. 均值漂移与卡尔曼滤波相结合的遥感影像道路中心线追踪算法[J]. 测绘学报, 2016, 45(2): 205-212.