Multiresponse Image Gathering and Restoration

  • Friedrich O. Huck
  • Carl L. Fales
  • Zia-ur Rahman
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 409)

Abstract

This chapter presents a method of image gathering and restoration that can produce images with spatial detail that is finer than the sampling interval. The method consists of an image-gathering process that acquires A images, each with a different SFR that extends beyond the sampling passband, and a Wienermatrix filter that unscrambles and reassembles the within-passband and aliased signal components. If the SNR is sufficiently high, then the resolution can be increased by a factor approaching \(1/\sqrt A \) times the sampling interval. However, practical applications may be rare, for this method requires, in addition to the high SNR, that the image-gathering device and the target remain stationary relative to each other during the image-gathering sequence or shift relative to each other by a known amount.

Keywords

Singular Point Spatial Frequency Sampling Interval Visual Quality Image Restoration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    C. L. Fales and F. O. Huck, An information theory of image gathering,“ Information Sciences 57–58, 245–285 (1991).MathSciNetCrossRefGoogle Scholar
  2. 2.
    R. Alter-Gartenberg, C. L. Fales, F. O. Huck, Z. Rahman and S. E. Reichenbach, “Multiresponse imaging: Information and fidelity,” Multidimensional Systems and Signal Processing 3, 81–102 (1992).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Friedrich O. Huck
    • 1
  • Carl L. Fales
    • 1
  • Zia-ur Rahman
    • 2
  1. 1.Research and Technology GroupNASA Langley Research CenterUSA
  2. 2.Department of Computer ScienceCollege of William & MaryUSA

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