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

Min Cheol Hong*, Moon Gi Kang, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

31 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1306-1316
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 1997
EventVisual Communications and Image Processing '97 - San Jose, CA, United States
Duration: Feb 12 1997Feb 12 1997


  • Iterative technique
  • Motion vector
  • Regularization parameter
  • Smoothing convex functional

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics


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