Extraction of coastline in high-resolution remote sensing images based on the active contour model

被引:2
|
作者
邢坤
付宜利
王树国
韩现伟
机构
[1] StateKeyLaboratoryofRoboticsandSystem,HarbinInstituteofTechnology
关键词
D O I
暂无
中图分类号
TP751 [图像处理方法];
学科分类号
摘要
While executing tasks such as ocean pollution monitoring,maritime rescue,geographic mapping,and automatic navigation utilizing remote sensing images,the coastline feature should be determined.Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image.Active contour model,also called snakes,have proven useful for interactive specification of image contours,so it is used as an effective coastlines extraction technique.Firstly,coastlines are detected by water segmentation and boundary tracking,which are considered initial contours to be optimized through active contour model.As better energy functions are developed,the power assist of snakes becomes effective.New internal energy has been done to reduce problems caused by convergence to local minima,and new external energy can greatly enlarge the capture region around features of interest.After normalization processing,energies are iterated using greedy algorithm to accelerate convergence rate.The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.
引用
收藏
页码:13 / 18
页数:6
相关论文
共 50 条
  • [41] Research on Coastline Automatic Extraction Methods Based on Remote Sensing Images
    Tian Wei
    Liu Wensong
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY AND MANAGEMENT SCIENCE (ITMS 2015), 2015, 34 : 699 - 705
  • [42] FARMLAND PARCELS EXTRACTION BASED ON HIGH RESOLUTION REMOTE SENSING IMAGES
    Hu, Tangao
    Zhu, Wenquan
    Zhang, Jinshui
    100 YEARS ISPRS ADVANCING REMOTE SENSING SCIENCE, PT 2, 2010, 38 : 304 - 308
  • [43] A novel FMH model for road extraction from high-resolution remote sensing images in urban areas
    Hong, Muzhu
    Guo, Junqi
    Dai, Yazhu
    Yin, Zhaoyang
    2018 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS, 2019, 147 : 49 - 55
  • [44] Scene classification of high-resolution remote sensing images based on IMFNet
    Zhang, Xin
    Wang, Yongcheng
    Zhang, Ning
    Xu, Dongdong
    Chen, Bo
    Ben, Guangli
    Wang, Xue
    JOURNAL OF APPLIED REMOTE SENSING, 2019, 13 (04)
  • [45] Multiconstraint Transformer-Based Automatic Building Extraction From High-Resolution Remote Sensing Images
    Yuan, Wei
    Ran, Weihang
    Shi, Xiaodan
    Shibasaki, Ryosuke
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 : 9164 - 9174
  • [46] Research on Road Extraction From High-Resolution Remote Sensing Images Based on Improved UNet plus
    Li, Ke
    Tan, Ming
    Xiao, Dexun
    Yu, Tiantian
    Li, Yanfeng
    Li, Ji
    IEEE ACCESS, 2024, 12 : 50300 - 50309
  • [47] House building extraction from high-resolution remote sensing images based on IEU-Net
    Wang Z.
    Zhou Y.
    Wang S.
    Wang F.
    Xu Z.
    National Remote Sensing Bulletin, 2021, 25 (11) : 2245 - 2254
  • [48] Rural Road Extraction from High-Resolution Remote Sensing Images Based on Geometric Feature Inference
    Liu, Jian
    Qin, Qiming
    Li, Jun
    Li, Yunpeng
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2017, 6 (10):
  • [49] High-Resolution Remote Sensing Image Building Extraction based on PRCUnet
    Xu J.
    Liu W.
    Shan H.
    Shi J.
    Li E.
    Zhang L.
    Li X.
    Liu, Wei (liuw@jsnu.edu.cn), 1838, Science Press (23): : 1838 - 1849
  • [50] Semantic Descriptions of High-Resolution Remote Sensing Images
    Wang, Binqiang
    Lu, Xiaoqiang
    Zheng, Xiangtao
    Li, Xuelong
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2019, 16 (08) : 1274 - 1278