The Comparative Study of Three Methods of Remote Sensing Image change detection

被引:0
|
作者
Xu, Lu [1 ]
He, Zongyi [1 ]
Zhang, Shaoqing [1 ]
Guo, Yan [1 ]
机构
[1] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China
关键词
Remote Sensing; Digital; Change Detection; Comparison Graphics;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper discusses three main methods of change detection: 1) Image subtraction method; 2) Image ratio method; 3) The method of change detection after classification. Firstly, the elimination method of influence factors of change detection is discussed. Then the basic principle of the three main methods is introduced and the experiments of the methods are carried on ERDAS software. At last, the analysis comparison is carried on and the relative merits and the applicable scope of the three methods are pointed out. Image subtraction method is a simple concept easy to understand and easy to use, a background value usually be repressed and a subtraction value often be enhanced in the result image. It is beneficial to information extraction, which value of the target and background is smaller, such as the beach zone, the ditch of estuaries. The main disadvantage is that it can not reflect which category is changed. Image ratio method is applicable to be used in change detection of city. Its disadvantage is also that it can not reflect which category is changed. The information of change property is provided in this method. The disadvantage is that the accuracy depends on the classification accuracy; it can not be used for the detail change detection of city.
引用
收藏
页码:612 / 615
页数:4
相关论文
共 50 条
  • [1] Remote sensing change detection: a comparative study of spectral distances
    Heydari, Hamed
    Nasrabadi, Sayyed Bagher Fatemi
    [J]. GEOCARTO INTERNATIONAL, 2023, 38 (01)
  • [2] Remote Sensing Image Change Detection With Transformers
    Chen, Hao
    Qi, Zipeng
    Shi, Zhenwei
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [3] Change Detection in Remote Sensing Image Data Comparing Algebraic and Machine Learning Methods
    Goswami, Anjali
    Sharma, Deepak
    Mathuku, Harani
    Gangadharan, Syam Machinathu Parambil
    Yadav, Chandra Shekhar
    Sahu, Saroj Kumar
    Pradhan, Manoj Kumar
    Singh, Jagendra
    Imran, Hazra
    [J]. ELECTRONICS, 2022, 11 (03)
  • [4] Remote Sensing Image Change Detection Combined With Saliency
    Zhang, Haitao
    Wang, Shilin
    Liu, Tao
    [J]. IEEE SENSORS JOURNAL, 2024, 24 (11) : 18108 - 18121
  • [5] REMOTE SENSING IMAGE REGRESSION FOR HETEROGENEOUS CHANGE DETECTION
    Luppino, Luigi T.
    Bianchi, Filippo M.
    Moser, Gabriele
    Anfinsen, Stian N.
    [J]. 2018 IEEE 28TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2018,
  • [6] A New Method in Change Detection of Remote Sensing Image
    Di Fengping
    Li Xiaowen
    Zhu Chongguang
    [J]. PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 1308 - +
  • [7] A new change detection method of remote sensing image
    Jia, Yonghong
    Xie, Zhiwei
    Lv, Zhen
    Zhu, Menghua
    Liu, Meijuan
    [J]. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2016, 41 (08): : 1001 - 1006
  • [8] Remote Sensing Image Change Saliency Detection Technology
    Yang, Shuai
    Zhao, Xi'an
    [J]. 3RD ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2018), 2018, 1069
  • [9] Research on target detection methods in remote sensing image
    Chen, Zhuo
    Meng, Xiangxu
    Wang, Xi
    [J]. PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON ADVANCED DESIGN AND MANUFACTURING ENGINEERING (ICADME 2017), 2017, 136 : 222 - 226
  • [10] Study on the Change Detection from High Resolution Remote-sensing Image
    Zhang, Zi-heng
    Tian, Yan
    Shao, Kui
    [J]. INTERNATIONAL CONFERENCE ON COMPUTER, NETWORK SECURITY AND COMMUNICATION ENGINEERING (CNSCE 2014), 2014, : 234 - 240