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Proceedings Paper

Super-resolution images from blurred observations
Author(s): Andy C. Yau; Michael Kwok-po Ng
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Paper Abstract

In this paper, we present a technique for generating a high- resolution image from a blurred image sequence. The image sequence consists of decimated, blurred and noisy versions of the high- resolution image. The high-resolution image is modeled as a Markov random field, and a maximum a posteriori estimation technique is used for image restoration. A fast algorithm based on Fast Fourier Transforms (FFTs) is derived to solve the resulting linear system. Numerical examples are given to illustrate the effectiveness of the method.

Paper Details

Date Published: 24 December 2003
PDF: 8 pages
Proc. SPIE 5205, Advanced Signal Processing Algorithms, Architectures, and Implementations XIII, (24 December 2003); doi: 10.1117/12.505015
Show Author Affiliations
Andy C. Yau, Univ. of Hong Kong (China)
Michael Kwok-po Ng, Univ. of Hong Kong (China)

Published in SPIE Proceedings Vol. 5205:
Advanced Signal Processing Algorithms, Architectures, and Implementations XIII
Franklin T. Luk, Editor(s)

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