Recursive MAP displacement estimation and restoration of noisy-blurred image sequences

James C. Brailean, Aggelos K Katsaggelos

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


In this paper, we develop a recursive model-based maximum a posieriori (MAP) estimator that simultaneously estimates the displacement vector field (DVF) and intensity field from a noisy-blurred image sequence. Current motion-compensated spatio-temporal filters treat the estimation of the DVF as a preprocessing step. Thus, no attempt is made to verify the accuracy of these estimates prior to their use in the filter. By simultaneously estimating these two fields, information is made available to each filter regarding the reliability of the estimates provided by the other filter. Nonstationary models are used for both the DVF and the intensity field in the proposed estimator, thus avoiding the smoothing of boundaries present in both.

Original languageEnglish (US)
Pages (from-to)384-395
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 1993
EventVisual Communications and Image Processing 1993 - Cambridge, MA, United States
Duration: Nov 7 1993Nov 7 1993

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Recursive MAP displacement estimation and restoration of noisy-blurred image sequences'. Together they form a unique fingerprint.

Cite this