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Selection of Optimal Stopping Time for Nonlinear Difusion Filtering

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Scale-Space and Morphology in Computer Vision (Scale-Space 2001)

Part of the book series: Lecture Notes in Computer Science 2106 ((LNCS,volume 2106))

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Abstract

We develop a novel time-selection strategy for iterative image restoration techniques: the stopping time is chosen so that the correlation of signal and noise in the filtered image is minimised. The new method is applicable to any images where the noise to be removed is uncorrelated with the signal; no other knowledge (e.g. the noise variance, training data etc.) is needed. We test the performance of our time estimation procedure experimentally, and demonstrate that it yields near-optimal results for a wide range of noise levels and for various filtering methods.

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References

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Author information

Authors and Affiliations

  1. Center for Machine Perception, Czech Technical University, Technická 2, 166 27, Czech Republic

    Pavel Mrázek⋆

Authors
  1. Pavel Mrázek⋆
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Editor information

Editors and Affiliations

  1. Dept. of Mathematics & Computer Science, University of Richmond, Richmond, VA, 23173, USA

    Michael Kerckhove

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© 2001 Springer-Verlag Berlin Heidelberg

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Mrázek⋆, P. (2001). Selection of Optimal Stopping Time for Nonlinear Difusion Filtering. In: Kerckhove, M. (eds) Scale-Space and Morphology in Computer Vision. Scale-Space 2001. Lecture Notes in Computer Science 2106, vol 2106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47778-0_26

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  • DOI: https://doi.org/10.1007/3-540-47778-0_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42317-1

  • Online ISBN: 978-3-540-47778-5

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