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Theoretical Development of Performance Bounds for Image Restoration

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Review of Progress in Quantitative Nondestructive Evaluation

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Abstract

As many image restoration techniques are continuing to be developed, it is increasingly difficult to compare the performance of various methods. Although some image-quality measures have been presented in the literature [1], it is inappropriate to choose a particular measure as a benchmark of performance evaluation for a wide range of applications. More importantly, none of these quality measures can be used as a performance bound which usually indicates how much potential performance can be improved for a specific restoration scheme. Therefore, it is extremely important to develop theoretical performance bounds under a variety of image and noise models for general image restoration schemes.

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References

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, 50011, USA

    Hsien-Sen Hung & John P. Basart

Authors
  1. Hsien-Sen Hung
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  2. John P. Basart
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Editor information

Editors and Affiliations

  1. Center for NDE Ames Laboratory (USDOE) and Department of Engineering Science and Mechanics, Iowa State University, 50011, Ames, Iowa, USA

    Donald O. Thompson

  2. Center for NDE and Department of Materials Science and Engineering, The Johns Hopkins University, 21218, Baltimore, Maryland, USA

    Dale E. Chimenti

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© 1990 Springer Science+Business Media New York

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Hung, HS., Basart, J.P. (1990). Theoretical Development of Performance Bounds for Image Restoration. In: Thompson, D.O., Chimenti, D.E. (eds) Review of Progress in Quantitative Nondestructive Evaluation. Review of Progress in Quantitative Nondestructive Evaluation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5772-8_89

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  • DOI: https://doi.org/10.1007/978-1-4684-5772-8_89

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-5774-2

  • Online ISBN: 978-1-4684-5772-8

  • eBook Packages: Springer Book Archive

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