Object Oriented Information Extraction from High Resolution Remote Sensing Imagery

被引：0
|
作者：
Ma, Hongbin [1 ]
Zhang, Cun [1 ]
Yang, Shengfei [1 ]
Xu, Junfang [1 ]
机构：
[1] Northeastern Univ, Coll Resource & Civil Engn, Shenyang, Peoples R China
来源：
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年
关键词：
multi-scale segmentation; high-resolution; object-oriented; information extraction; eCognition;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the wide use of high-resolution remote sensing image, the technology of object-oriented information extraction from high resolution imagery has been developed rapidly. In this paper, mainly used eCognition software and selected image of HuShiTai in Shen Yang as study area, made use of object-oriented technology to extract features information. Finally the information result is compared with traditional schemes. The contrastive result shows that object-oriented technology can overcome the phenomenon of "salt and pepper" which happened in traditional classification, the accuracy of extraction has been greatly improved relative to traditional method and object-oriented technology provides an effective way for the utilization of high-resolution image.
引用
收藏
页码：1128 / 1132
页数：5
相关论文
共 50 条
  • [21] Greenhouse extraction with high-resolution remote sensing imagery using fused fully convolutional network and object-oriented image analysis
    Ma, Hairong
    Feng, Tianjing
    Shen, Xiangcheng
    Luo, Zhiqing
    Chen, Pingting
    Guan, Bo
    JOURNAL OF APPLIED REMOTE SENSING, 2021, 15 (04)
  • [22] Semisupervised Building Instance Extraction From High-Resolution Remote Sensing Imagery
    Fang, Fang
    Xu, Rui
    Li, Shengwen
    Hao, Qingyi
    Zheng, Kang
    Wu, Kaishun
    Wan, Bo
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [23] A new method of road extraction from high-resolution remote sensing imagery
    Ni, Cui
    Guan, Zequn
    Ye, Qin
    SIXTH INTERNATIONAL SYMPOSIUM ON DIGITAL EARTH: MODELS, ALGORITHMS, AND VIRTUAL REALITY, 2010, 7840
  • [24] A methodology for urban roads network extraction from high resolution remote sensing imagery
    Tao, C. (kingtaochao@csu.edu.cn), 1600, Central South University of Technology (44):
  • [25] Building Extraction From Remote Sensing Imagery With a High-Resolution Capsule Network
    Yu, Yongtao
    Liu, Chao
    Gao, Junyong
    Jin, Shenghua
    Jiang, Xiaoling
    Jiang, Mingxin
    Zhang, Haiyan
    Zhang, Yahong
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [26] Object-oriented classification approach for remote sensing imagery information extraction in loess hilly-gully region
    Mai, Kaile
    Zhang, Wenhui
    Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery, 2011, 42 (04): : 153 - 158
  • [27] Impact Analysis of Different Spatial Resolution DEM on Object-Oriented Landslide Extraction from High Resolution Remote Sensing Images
    Chen, Qihao
    Liu, Xiuguo
    Liu, Chen
    Ji, Rui
    2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 940 - 945
  • [28] DENSE GREENHOUSE EXTRACTION IN HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGERY
    Chen, Dingyuan
    Zhong, Yanfei
    Ma, Ailong
    Cao, Liqin
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 4092 - 4095
  • [29] OBJECT ORIENTED HIERARCHICAL CLASSIFICATION OF HIGH RESOLUTION REMOTE SENSING IMAGES
    Ons, Ghariani
    Tebourbi, Riadh
    2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 1681 - 1684
  • [30] Contour-oriented Cropland Extraction from High Resolution Remote Sensing Imagery Using Richer Convolution Features Network
    Liu, Hao
    Luo, Jiancheng
    Sun, Yingwei
    Xia, Liegang
    Wu, Wei
    Yang, Haiping
    Hu, Xiaodong
    Gao, Lijing
    2019 8TH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS), 2019,
12345