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Proceedings Paper

Regularized multichannel restoration approach for globally optimal high-resolution video sequence
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Paper Abstract

This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.

Paper Details

Date Published: 10 January 1997
PDF: 11 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263211
Show Author Affiliations
Min-Cheol Hong, Northwestern Univ. (United States)
Moon Gi Kang, Univ. of Minnesota/Duluth (United States)
Aggelos K. Katsaggelos, Northwestern Univ. (United States)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp III, Editor(s)

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