Welcome to Journal of Beijing Institute of Technology
Volume 28Issue 2
.
Turn off MathJax
Article Contents
Bo Wang, Changqing Li, Shi Tang, Zhiqiang Zhou, Hong Zhao. Accurate Registration of Remote Sensing Images Based on Local Optimal Transformation[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2019, 28(2): 371-382. doi: 10.15918/j.jbit1004-0579.17190
Citation: Bo Wang, Changqing Li, Shi Tang, Zhiqiang Zhou, Hong Zhao. Accurate Registration of Remote Sensing Images Based on Local Optimal Transformation[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2019, 28(2): 371-382.doi:10.15918/j.jbit1004-0579.17190

Accurate Registration of Remote Sensing Images Based on Local Optimal Transformation

doi:10.15918/j.jbit1004-0579.17190
  • Received Date:2017-12-15
  • As the basic work of image stitching and object recognition, image registration played an important part in the image processing field. Much previous work in registration accuracy and real-time performance progressed very slowly, especially in registrating images with line feature. An innovative method for image registration based on lines is proposed, it can effectively improve the accuracy and real-time performance of image registration. The line feature can deal with some registration problems where point feature does not work. Our registration process is divided into two parts. The first part determines the rough registration transformation relation between reference image and test image. Then the similarity degree among different transformation and modified non-maximum suppression (MNMS) algorithms are obtained, which produce local optimal solution to optimize the rough registration transformation. The final optimal registration relation can be obtained from two registration parts according to the match scores. The experimental results show that the proposed method makes a more accurate registration relation and performs better in real-time situation.
  • loading
  • [1]
    Lowe D G. Distinctive image features from scale-invariant keypoints[M]. Dordrecht:Kluwer Academic Publishers, 2004.
    [2]
    Hossain M T, Lu G, Teng S W, et al. Improved symmetric-SIFT for multi-modal image registration[C]//International Conference on Digital Image Computing:Techniques and Applications DBLP, 2011:197-202.
    [3]
    Bay H, Ess A, Tuytelaars T, et al. Speeded-up robust features (SURF)[J]. Computer Vision & Image Understanding, 2008, 110(3):346-359.
    [4]
    Habib A F, Alruzouq R I. Line-based modified iterated Hough transform for automatic registration of multi-source imagery[J]. Photogrammetric Record, 2004, 19(105):5-21.
    [5]
    Youngwook Paul Kwon. Line segment-based aerial image registration[D].California:University of California at Berkeley,2014:25-26.
    [6]
    Zhao C, Goshtasby A A. Registration of multitemporal aerial optical images using line features[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 117:149-160. \
    [7]
    Li Yong, Stevenson R L. Multimodal image registration with line segments by selective search[J]. IEEE Transactions on Cybernetics, 2016, 47(5):1285-1298.
    [8]
    Canny J. A computational approach to edge detection [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986(6):679-698.
  • 加载中

Catalog

    通讯作者:陈斌, bchen63@163.com
    • 1.

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (393) PDF downloads(296) Cited by()
    Proportional views
    Related

    /

      Return
      Return
        Baidu
        map