Theoretical Development of Performance Bounds for Image Restoration

  • Hsien-Sen Hung
  • John P. Basart
Part of the Review of Progress in Quantitative Nondestructive Evaluation book series


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.


Original Image Point Spread Function Fisher Information Noise Model Unbiased Estimator 
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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Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • Hsien-Sen Hung
    • 1
  • John P. Basart
    • 1
  1. 1.Department of Electrical and Computer EngineeringIowa State UniversityAmesUSA

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