A coarse-to-fine correction method for seriously oblique remote sensing image

被引:0
|
作者
Wang, Chunyuan [1 ]
Gu, Yanfeng [1 ]
Zhang, Ye [1 ]
机构
[1] School of Electronics and Information Engineering, Harbin Institute of Technology, Box. 314, No. 92, West Da-Zhi Street, Harbin 150001, China
来源
ICIC Express Letters | 2011年 / 5卷 / 12期
关键词
Geometry - Remote sensing - Electromagnetic wave attenuation - Optical resolving power - Pore pressure;
D O I
暂无
中图分类号
学科分类号
摘要
Conventional approaches are unsuitable to effectively correct the image ac quired in the seriously oblique condition which is susceptible to resolution disparity. Considering that the variability of geometric distortion and the control points' distribution play important roles in correction accuracy, this paper introduces a coarse-to-fine procedure for correcting large-angle images. Firstly, the coarse procedure adopts a control points-constrained piecewise polynomial algorithm to geometric correction with control points clustering, where the whole image is partitioned into contiguous subparts which are respectively corrected by different polynomial correction formulae. And in the fine procedure, for compensating the unreliability of the rigid transformation, a nonrigid thin-plate splines model is used for correcting the whole image. The experimental results show that the proposed correction method is significantly outperforming conventional approaches especially in non-flat areas. © 2011 ICIC International.
引用
收藏
页码:4503 / 4509
相关论文
共 50 条
  • [31] A Coarse-to-Fine Two-Stage Attentive Network for Haze Removal of Remote Sensing Images
    Li, Yufeng
    Chen, Xiang
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (10) : 1751 - 1755
  • [32] Coarse-to-Fine: A Layered Sensing Approach to Situational Awareness
    Watson, Edward A.
    2009 CONFERENCE ON LASERS AND ELECTRO-OPTICS AND QUANTUM ELECTRONICS AND LASER SCIENCE CONFERENCE (CLEO/QELS 2009), VOLS 1-5, 2009, : 3253 - 3254
  • [33] A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery
    Guo, Haonan
    Du, Bo
    Zhang, Liangpei
    Su, Xin
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2022, 183 : 240 - 252
  • [34] Progressive decomposition: a method of coarse-to-fine image parsing using stacked networks
    Yunhan Sun
    Jiagao Hu
    Jinlong Shi
    Zhengxing Sun
    Multimedia Tools and Applications, 2020, 79 : 13379 - 13402
  • [35] Look Twice and Closer: A Coarse-to-Fine Segmentation Network for Small Objects in Remote Sensing Images
    Chen, Silin
    Wang, Qingzhong
    Di, Kangjian
    Xiong, Haoyi
    Zou, Ningmu
    IEEE SIGNAL PROCESSING LETTERS, 2025, 32 : 826 - 830
  • [36] A coarse-to-fine image registration method based on autocorrelation structural difference information
    Pang, Bo
    Wang, Lei
    Yang, Qili
    Gao, Haiyun
    Wu, Chunjun
    Zhu, Wenlei
    REMOTE SENSING LETTERS, 2025, 16 (02) : 181 - 190
  • [37] Progressive decomposition: a method of coarse-to-fine image parsing using stacked networks
    Sun, Yunhan
    Hu, Jiagao
    Shi, Jinlong
    Sun, Zhengxing
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (19-20) : 13379 - 13402
  • [38] PROGRESSIVE REFINEMENT: A METHOD OF COARSE-TO-FINE IMAGE PARSING USING STACKED NETWORK
    Hu, Jiagao
    Sun, Zhengxing
    Sun, Yunhan
    Shi, Jinlong
    2018 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2018,
  • [39] A SELF-ADJUSTIVE GEOMETRIC CORRECTION METHOD FOR SERIOUSLY OBLIQUE AERO IMAGE
    Wang, Chunyuan
    Zhang, Ye
    Liu, Pigang
    Xu, Qi
    Gu, Yanfeng
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1433 - 1436
  • [40] Coarse-to-fine image registration for sweep fingerprint sensors
    Zhang, Yong-liang
    Yang, Jie
    Wu, Hong-tao
    OPTICAL ENGINEERING, 2006, 45 (06)