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

Min-Cheol Hong; Moon Gi Kang; Aggelos K. Katsaggelos

doi:10.1117/12.263211

10 January 1997 Regularized multichannel restoration approach for globally optimal high-resolution video sequence

Min-Cheol Hong, Moon Gi Kang, Aggelos K. Katsaggelos

Proceedings Volume 3024, Visual Communications and Image Processing '97; (1997) https://doi.org/10.1117/12.263211
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

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.

Citation Download Citation

Min-Cheol Hong, Moon Gi Kang, and Aggelos K. Katsaggelos "Regularized multichannel restoration approach for globally optimal high-resolution video sequence", Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); https://doi.org/10.1117/12.263211

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