Multiframe super-resolution reconstruction of small moving objects

  • Authors:

  • Adam W. M. van Eekeren;Klamer Schutte;Lucas J. van Vliet

  • Affiliations:

  • TNO Defence, Security, and Safety, The Hague, The Netherlands and Delft University of Technology, Delft, The Netherlands;TNO Defence, Security and Safety, The Hague, The Netherlands;Delft University of Technology, Delft, The Netherlands

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 2010

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Abstract

Multiframe super-resolution (SR) reconstruction of small moving objects against a cluttered background is difficult for two reasons: a small object consists completely of "mixed" boundary pixels and the background contribution changes from frame-to-frame. We present a solution to this problem that greatly improves recognition of small moving objects under the assumption of a simple linear motion model in the real-world. The presented method not only explicitly models the image acquisition system, but also the space-time variant fore- and background contributions to the "mixed" pixels. The latter is due to a changing local background as a result of the apparent motion. The method simultaneously estimates a subpixel precise polygon boundary as well as a high-resolution (HR) intensity description of a small moving object subject to a modified total variation constraint. Experiments on simulated and real-world data show excellent performance of the proposed multiframe SR reconstruction method.