Multidimensional Systems and Signal Processing

, Volume 18, Issue 2–3, pp 173–188 | Cite as

An efficient algorithm for superresolution in medium field imaging

  • Andy C. Yau
  • N. K. Bose
  • Michael K. Ng
Original Article


In this paper, we study the problem of reconstruction of a high-resolution (HR) image from several blurred low-resolution (LR) image frames in medium field. The image frames consist of blurred, decimated, and noisy versions of a HR image. The HR image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a HR image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore HR images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.


Superresolution Medium field Preconditioned conjugate gradient method Fast Fourier transforms Toeplitz matrix Deblussing 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department of MathematicsThe University of Hong KongHong KongHong Kong
  2. 2.Department of Electrical Engineering, The Spatial and Temporal Signal Processing CenterThe Pennsylvania State UniversityUniversity ParkU.S.A
  3. 3.Department of MathematicsHong Kong Baptist UniversityKowloon TongHong Kong

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