Super-resolution image reconstruction from a sequence of aliased imagery

S. Susan Young, Ronald G. Driggers

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

This paper presents a super-resolution image reconstruction from a sequence of aliased imagery. The sub-pixel shifts (displacement) among the images are unknown due to uncontrolled natural jitter of the imager. A correlation method is utilized to estimate sub-pixel shifts between each low-resolution aliased image with respect to a reference image. An error-energy reduction algorithm is derived to reconstruct the high-resolution alias-free output image. The main feature of this proposed error-energy reduction algorithm is that we treat the spatial samples from low-resolution images that possess unknown and irregular (uncontrolled) sub-pixel shifts as a set of constraints to populate an over-sampled (sampled above the desired output bandwidth) processing array. The estimated sub-pixel locations of these samples and their values constitute a spatial domain constraint. Furthermore, the bandwidth of the alias-free image (or the sensor imposed bandwidth) is the criterion used as a spatial frequency domain constraint on the over-sampled processing array. The results of testing the proposed algorithm on the simulated low-resolution aliased images from real world non-aliased FLIR (Forward-Looking Infrared) images, real world aliased FLIR images and visible aliased images are provided.

Original languageEnglish (US)
Article number18
Pages (from-to)114-124
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5784
DOIs
StatePublished - 2005
Externally publishedYes
EventInfrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI - Orlando, FL, United States
Duration: Mar 30 2005Apr 1 2005

Keywords

  • Aliased imagery
  • Error-energy reduction
  • Sub-pixel shift estimation
  • Super-resolution image reconstruction

ASJC Scopus subject areas

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

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