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Algorithm and Constraints for Exact Non-blind Deconvolution

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Abstract

Image filtering is generally an irreversible process. Image restoration methods, such as inverse filtering or other deconvolution techniques, cannot precisely recover the original image and often introduce some level of artifacts. In the current paper, we formulate the filtering as a blending of several transformed replications of the original image. We assume zero noise after the filtering. Using this convention, we propose a method that precisely restores the original image from its filtered version. The method is applicable for a family of filters including average box filters and approximated Gaussian filters.

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Authors and Affiliations

  1. Computational Radiology Laboratory, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    Yechiel Lamash

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  1. Yechiel Lamash
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Correspondence to Yechiel Lamash.

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Lamash, Y. Algorithm and Constraints for Exact Non-blind Deconvolution. J Math Imaging Vis 60, 692–706 (2018). https://doi.org/10.1007/s10851-017-0784-7

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  • DOI: https://doi.org/10.1007/s10851-017-0784-7

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