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Maximum entropy algorithm applied to image enhancement

Maximum entropy algorithm applied to image enhancement

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© The Institution of Electrical Engineers
Published

A model is suggested for assigning the prior probability of an image in Bayes' theorem which leads to a very general algorithm for image enhancement. Examples of sharpening blurred photographs show how the success of deconvolution depends on the signal/noise ratio in the degraded images.

Inspec keywords: picture processing

Other keywords: maximum entropy algorithm; Bayes' theorem; deconvolution; image enhancement

Subjects: Optical information, image and video signal processing; Pattern recognition

References

    1. 1)
      • B.R. Frieden . Restoring with maximum likelihood and maximum entrop. J. Opt. Soc. Am. , 511 - 518
    2. 2)
      • S.F. Gull , G.J. Daniel . Image reconstruction from incomplete and noisy data. Nature , 686 - 690
    3. 3)
      • J. Skilling , A.W. Strong , K. Bennett . Maximum-entropy image processing in gamma-ray astronomy. Mon. Not. R. Astron. Soc. , 761 - 768
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