This article is part of the series Super-Resolution Imaging: Analysis, Algorithms, and Applications.

Open Access Research Article

Video-to-Video Dynamic Super-Resolution for Grayscale and Color Sequences

Sina Farsiu1*, Michael Elad2 and Peyman Milanfar1

  • * Corresponding author: Sina Farsiu

Author Affiliations

1 Electrical Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA

2 Computer Science Department, Technion – Israel Institute of Technology, Haifa 32000, Israel

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EURASIP Journal on Advances in Signal Processing 2006, 2006:061859  doi:10.1155/ASP/2006/61859

The electronic version of this article is the complete one and can be found online at:

Received: 17 December 2004
Revisions received: 10 March 2005
Accepted: 15 March 2005
Published: 8 February 2006

© 2006 Farsiu et al.

We address the dynamic super-resolution (SR) problem of reconstructing a high-quality set of monochromatic or color super-resolved images from low-quality monochromatic, color, or mosaiced frames. Our approach includes a joint method for simultaneous SR, deblurring, and demosaicing, this way taking into account practical color measurements encountered in video sequences. For the case of translational motion and common space-invariant blur, the proposed method is based on a very fast and memory efficient approximation of the Kalman filter (KF). Experimental results on both simulated and real data are supplied, demonstrating the presented algorithms, and their strength.


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