• DocumentCode
    2382227
  • Title

    Spatial-spectral cross correlation for reliable multispectral image registration

  • Author

    Yang, Zhengwei ; Shen, Guangrong ; Wang, Wei ; Qian, Zhenhua ; Ke, Ying

  • Author_Institution
    R&D Div., USDA, Fairfax, VA, USA
  • fYear
    2009
  • fDate
    14-16 Oct. 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents a normalized spatial-spectral cross correlation method for multispectral image registration. This method generalized correlation coefficients defined in a spatial domain or a spectral domain into a spatial-spectral domain. This novel spatial-spectral signature based method significantly increases the discrimination of the correlation coefficient for a given template window size, increases the registration reliability, robustness and accuracy, as compared with the classic normalized spatial cross correlation method. It is invariant to the dynamic range and robust to the noise yet it is straightforward with minimum preprocessing required. The experimental results show that the normalized spatial-spectral cross correlation method is superior to the traditional normalized spatial cross correlation method in effective registering multispectral images. However, the experimental results also show that only those statistically highly independent spectral bands are helpful for enhancing the robustness and reliability of the NSSCC multispectral image registration. Specifically, it is found that the near infrared band together with visual bands will gives the best registration results.
  • Keywords
    correlation theory; image registration; reliability theory; visual databases; correlation coefficients; reliable multispectral image registration; spatial spectral cross correlation; spatial spectral signature; spectral domain; Correlation; Image registration; Layout; Multispectral imaging; Noise robustness; Pattern matching; Radiometry; Research and development; Shape; US Department of Agriculture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop (AIPRW), 2009 IEEE
  • Conference_Location
    Washington, DC
  • ISSN
    1550-5219
  • Print_ISBN
    978-1-4244-5146-3
  • Electronic_ISBN
    1550-5219
  • Type

    conf

  • DOI
    10.1109/AIPR.2009.5466291
  • Filename
    5466291