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Design of a new restoration algorithm based on the constrained mean-square-error criterion

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Abstract

In this paper the joint optimization of different criteria is addressed, as a powerful means of incorporatinga priori information in linear image-restoration algorithms. Theconstrained mean-square-error (CMSE) approach is introduced, which enables the incorporation of both spatial and spectral information regarding the peculiarities of the problem. Depending on the nature of the spatial information, this approach can be interpreted as either a regularized or an adaptive scheme. As a regularized scheme, it offers an alternative to conventional approaches, in which the ringing artifacts are efficiently suppressed by means of the regularizing operator. As an adaptive scheme, the CMSE approach offers the flexibility of applying either linear Wiener filtering or inverse filtering, depending on the local signal activity. Optimal techniques for the selection of the regularization parameter in both nonadaptive and adaptive cases are introduced. The capabilities of the CMSE approach as a regularized scheme and an adaptive scheme, are demonstrated through restoration examples.

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Authors and Affiliations

  1. Department of Computer Engineering, University of Minnesota, 271 Marshall W. Alworth Hall, 10 University Drive, 55812-2496, Duluth, MN

    M. E. Zervakis

  2. Department of Electrical Engineering, University of Toronto, 35 St. George St., M5S 1A4, Toronto, Ontario, Canada

    A. N. Venetsanopoulos

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  1. M. E. Zervakis
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  2. A. N. Venetsanopoulos
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Zervakis, M.E., Venetsanopoulos, A.N. Design of a new restoration algorithm based on the constrained mean-square-error criterion. Multidim Syst Sign Process 3, 381–408 (1992). https://doi.org/10.1007/BF01940232

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  • DOI: https://doi.org/10.1007/BF01940232

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