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The Computer Journal Advance Access originally published online on October 17, 2007
The Computer Journal 2009 52(1):1-14; doi:10.1093/comjnl/bxm041
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© The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Restoration of Bayer-sampled Image Sequences

Murat Gevrekci1, Bahadir K. Gunturk1 and Yucel Altunbasak2,*

1 Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA 70803, USA
2 Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

* Corresponding author: yucel{at}ece.gatech.edu

Received 21 May 2006; revised 23 April 2007

Spatial resolution of digital images are limited due to optical/sensor blurring and sensor site density. In single-chip digital cameras, the resolution is further degraded because such devices use a color filter array to capture only one spectral component at a pixel location. The process of estimating the missing two color values at each pixel location is known as demosaicking. Demosaicking methods usually exploit the correlation among color channels. When there are multiple images, it is possible not only to have better estimates of the missing color values but also to improve the spatial resolution further (using super-resolution reconstruction). In this paper, we propose a multi-frame spatial resolution enhancement algorithm based on the projections onto convex sets technique.

Key Words: demosaicking • super-resolution • image processing


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