• DocumentCode
    3201631
  • Title

    Joint image registration and super-resolution based on combinational coefficient matrix

  • Author

    Rezayi, Hossein ; Seyedin, Seyed Alireza

  • Author_Institution
    Ferdowsi Univ. of Mashhad, Mashhad, Iran
  • fYear
    2015
  • fDate
    11-12 March 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    In this paper we propose a new joint image registration (IR) and super-resolution (SR) method by combining the three principal operations of warping, blurring and down-sampling. Unlike previous methods, we neither calculate the Jacobian matrix numerically nor derive the Jacobian matrix by treating the three principal operations separately. We develop a new approach to derive the Jacobian matrix analytically from the combination of the three principal operations. Experimental results show that our method has better Peak Signal-to-Noise Ratio (PSNR) than the recently proposed Tian´s joint method of IR and SR. Computational complexity also has been decreased in our proposed method.
  • Keywords
    Jacobian matrices; combinatorial mathematics; computational complexity; image registration; image resolution; image restoration; Jacobian matrix; PSNR; combinational coefficient matrix; computational complexity; down-sampling; image blurring; image registration; image warping; peak signal-to-noise ratio; super-resolution; Cost function; Image reconstruction; Image resolution; Jacobian matrices; Joints; Kernel; Mathematical model; Combinational operation; Jacobian matrix; Super-Resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition and Image Analysis (IPRIA), 2015 2nd International Conference on
  • Conference_Location
    Rasht
  • Print_ISBN
    978-1-4799-8444-2
  • Type

    conf

  • DOI
    10.1109/PRIA.2015.7161636
  • Filename
    7161636