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Deconvolution with partially known kernel of nonnegative signals

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Abstract

This paper extends the Bayesian direct deconvolution method to the case in which the convolution kernel depends on few unknown nuisance parameters. Moreover, an acceleration procedure is proposed that drastically reduces the computational burden. Finally, the implementation of the method by means of the fast Fourier transform is fully discussed in the multidimensional case.

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Authors and Affiliations

  1. Istituto per le Applicazioni del Calcolo “M. Picone,”, C.N.R., Viale del Policlinico 137, 00161, Roma, Italy

    F. Barone

  2. Dipartimento di Matematica, Università di Roma “Tor Vergata,”, Via O. Raimondo, 00173, Roma, Italy

    C. Rossi

Authors
  1. F. Barone
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  2. C. Rossi
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Barone, F., Rossi, C. Deconvolution with partially known kernel of nonnegative signals. Machine Vis. Apps. 3, 107–115 (1990). https://doi.org/10.1007/BF01212194

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