Image motion restoration from a sequence of images

Ofer Hadar, Matthew Robbins, Yehuda Novogrozky, David Kaplan

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


The restoration of images blurred as a result of image motion or vibration is discussed. The key to the success of the restoration algorithm is accurately determining the optical transfer function (OTF) representing the image motion degradation in the spatial frequency domain. The basic method of obtaining the OTF from the measured function of relative displacement between the camera and the object using a motion sensor has been developed recently and is discussed elsewhere (Sezan and Lagendijk, 1993). The motion function is derived instead from an analysis of a sequence of consecutive images. The first step is to obtain the image motion information from the sequence of images according to two well-known algorithms - the block-matching algorithm (BMA) and the edge trace tracking (ETT). The basis for these two methods consists of tracking a block or an edge through a sequence of several consecutive images. Results of these two methods were fitted to a sinusoidal vibration function and compared; there was excellent agreement between them. Finally, the image is restored using the OTF estimated via the tracking method.

Original languageEnglish
Article number24125
Pages (from-to)2898-2904
Number of pages7
JournalOptical Engineering
Issue number10
StatePublished - 1 Jan 1996


  • Image motion
  • Image restoration
  • Image vibration
  • Optical transfer function

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (all)


Dive into the research topics of 'Image motion restoration from a sequence of images'. Together they form a unique fingerprint.

Cite this