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A Fast Algorithm for Image Super-Resolution from Blurred Observations

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Author(s): Bose Nirmal K | Ng Michael K | Yau Andy C

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2006;
Issue: 1;
Start page: 035726;
Date: 2006;
Original page

ABSTRACT
We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a 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, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.

Tango Jona
Tangokurs Rapperswil-Jona

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