Super-Resolution Image Restoration from Blurred Low-Resolution Images

Authors:
Michael K. Ng;Andy C. Yau
Affiliations:
Department of Mathematics, The University of Hong Kong;Department of Mathematics, The University of Hong Kong
Venue:
Journal of Mathematical Imaging and Vision
Year:
2005

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Abstract

In this paper, we study the problem of reconstructing a high-resolution image from several blurred low-resolution image frames. The image frames consist of decimated, blurred and noisy versions of the high-resolution image. The high-resolution 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, the high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore the high-resolution image. Computer simulations are given to illustrate the effectiveness of the proposed method.