Regularized blur-assisted displacement field estimation

Damon L. Tull*, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

15 Scopus citations


Due to the finite acquisition time of practical cameras, objects can move during image acquisition, therefore introducing motion blur degradations. Traditionally, these degradations are treated as undesirable artifacts that should be removed before further processing. In this work, we consider the use of motion blur as an indication of scene motion. We present two robust regularized motion estimation algorithms that consider the use of (motion) blur in their formulation. The first algorithm uses motion blur as prior knowledge for the estimation of the motion field. The second algorithm considers the joint estimation of the motion and motion blur. Each approach results in a motion blur point spread field, a motion field and a restored image in an approach that is different from previous work. Preliminary results are presented.

Original languageEnglish (US)
Number of pages4
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: Sep 16 1996Sep 19 1996


OtherProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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