• DocumentCode
    1797807
  • Title

    IR remote sensing image registration based on multi-scale feature extraction

  • Author

    Jun Kong ; Min Jiang ; Yi-Ning Sun

  • Author_Institution
    Key Lab. of Adv. Process Control for Light Ind., Jiangnan Univ., Wuxi, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1352
  • Lastpage
    1358
  • Abstract
    Infrared remote sensing image has poor contrast and lower SNR so that real-time and robustness are not superior in image registration. In order to solve it, a novel registration based on Multi-scale feature extraction is proposed in this paper. This algorithm is designed in two aspects. Firstly, Gaussian convolution template size adjusts adaptively with the increasing of scale factors. Then the Multi-space is reconstructed. Secondly, feature points bidirectional matching based on the City-block distance is introduced into image registration. So the real-time performance and robustness are enhanced further. Finally, the experimental results showed that by this improved algorithm the infrared remote sensing images are registered more quickly and accurately than by traditional SIFT algorithm.
  • Keywords
    feature extraction; geophysical image processing; image matching; image reconstruction; image registration; infrared imaging; remote sensing; Gaussian convolution template size; IR remote sensing image registration; SIFT algorithm; SNR; city-block distance; feature points bidirectional matching; infrared remote sensing; multiscale feature extraction; multispace reconstruction; scale factors; scale-invariant feature transform; signal-to-noise ratio; Feature extraction; Image reconstruction; Image registration; Real-time systems; Remote sensing; Robustness; Vectors; IR remote sensing image; Multi-scale; feature points; registration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889630
  • Filename
    6889630