On the Appropriate Feature for General SAR Image Registration

被引:0
|
作者
Li, Dong [1 ]
Zhang, Yunhua [1 ]
机构
[1] Chinese Acad Sci, Ctr Space Sci & Appl Res, Key Lab Microwave Remote Sensing, Beijing 100190, Peoples R China
来源
SAR IMAGE ANALYSIS, MODELING, AND TECHNIQUES XII | 2012年 / 8536卷
关键词
Feature detector; feature descriptor; image registration; speeded up robust feature (SURF); subpixel accuracy; synthetic aperture radar (SAR); COREGISTRATION; INTERFEROMETRY; ACCURACY;
D O I
10.1117/12.970520
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed, the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation, and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for general SAR image registration.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Robust Optical and SAR Multi-sensor Image Registration
    Wu, Yingdan
    Ming, Yang
    SAR IMAGE ANALYSIS, MODELING, AND TECHNIQUES XV, 2015, 9642
  • [32] Local convolutional features and metric learning for SAR image registration
    Qiangliang Guo
    Jin Xiao
    Xiaoguang Hu
    Baochang Zhang
    Cluster Computing, 2019, 22 : 3103 - 3114
  • [33] Multifeature Alignment and Matching Network for SAR and Optical Image Registration
    Hu, Xin
    Wu, Yan
    Li, Zhikang
    Yang, Zhifei
    Li, Ming
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2025, 18 : 352 - 367
  • [34] Local convolutional features and metric learning for SAR image registration
    Guo, Qiangliang
    Xiao, Jin
    Hu, Xiaoguang
    Zhang, Baochang
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (02): : S3103 - S3114
  • [35] OS-PC: Combining Feature Representation and 3-D Phase Correlation for Subpixel Optical and SAR Image Registration
    Xiang, Yuming
    Tao, Rongshu
    Wan, Ling
    Wang, Feng
    You, Hongjian
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 58 (09): : 6451 - 6466
  • [36] Combining Optimized SAR-SIFT Features and RD Model for Multisource SAR Image Registration
    Wang, Mengmeng
    Zhang, Jixian
    Deng, Kazhong
    Hua, Fenfen
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [37] SAR image registration based on Susan algorithm
    Wang, Chun-bo
    Fu, Shao-hua
    Wei, Zhong-yi
    INTERNATIONAL SYMPOSIUM ON LIDAR AND RADAR MAPPING 2011: TECHNOLOGIES AND APPLICATIONS, 2011, 8286
  • [38] Feature based image registration and mosaicing
    Song, WL
    Wang, H
    ENHANCED AND SYNTHETIC VISION 2000, 2000, 4023 : 260 - 268
  • [39] An Assisted Method for Multitemporal SAR Image Registration
    Chen, Zhengyu
    Xiao, Ruya
    Gao, Xiaoyuan
    Liang, Dong
    Zhang, Dezhi
    Sun, Jingyi
    IEEE JOURNAL ON MINIATURIZATION FOR AIR AND SPACE SYSTEMS, 2025, 6 (01): : 36 - 43
  • [40] SAR Image Registration Based on SIFT and MSA
    Yi Zhaoxiang
    Zhang Xiongmei
    Mu Xiaodong
    Wang Kui
    Song Jianshe
    SELECTED PAPERS FROM CONFERENCES OF THE PHOTOELECTRONIC TECHNOLOGY COMMITTEE OF THE CHINESE SOCIETY OF ASTRONAUTICS: OPTICAL IMAGING, REMOTE SENSING, AND LASER-MATTER INTERACTION 2013, 2014, 9142