Multichannel regularized iterative restoration of motion compensated image sequences

Mun Gi Choi*, Nikolas P. Galatsanos, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Restoration of image sequences is an important problem that can be encountered in many image processing applications, such as visual communications, robot guidance, and target tracking. The independent restoration of each frame in an image sequence is a suboptimal approach because the between-frame correlations are not explicitly taken into consideration. In this paper we address this problem by proposing a multichannel restoration approach. The multiple time-frames (channels) of the image sequence are restored simultaneously by using a multichannel regularized least-squares formulation of the problem. The regularization operator captures both within- and between-frame (channel) properties of the image sequence with the explicit use of the displacement vector field. We propose a number of different approaches to obtain the multichannel regularization operator, as well as an algorithm to iteratively compute the restored images. We present experiments that demonstrate the value of the proposed multichannel approach.

Original languageEnglish (US)
Pages (from-to)244-258
Number of pages15
JournalJournal of Visual Communication and Image Representation
Issue number3
StatePublished - Sep 1996

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


Dive into the research topics of 'Multichannel regularized iterative restoration of motion compensated image sequences'. Together they form a unique fingerprint.

Cite this