A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior - Comment (Articolo in rivista)

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  • A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior - Comment (Articolo in rivista) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • Achim A.; Kuruoglu E. E.; Bezerianos A.; Tsakalides P. (2007)
    A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior - Comment
    in Pattern recognition letters
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Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Achim A.; Kuruoglu E. E.; Bezerianos A.; Tsakalides P. (literal)
Pagina inizio
  • 1845 (literal)
Pagina fine
  • 1847 (literal)
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  • 28 (literal)
Rivista
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  • In: Pattern Recognition Letters, vol. 28 (13) pp. 1845 - 1847. Elsevier, 2007. (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • University of Bristol, ISTI-CNR, University of Patras, ICT-FORTH (literal)
Titolo
  • A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior - Comment (literal)
Abstract
  • The purpose of this commentary is to point out that the paper by Boubchir and Fadili (B-F) [Boubchir, L., Fadili, J.M., 2006. A closedform nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior. Pattern Recognit. Lett. 27, 1370-1382] is little more than a paraphrase of earlier work in [Achim, A., Bezerianos, A., Tsakalides, P., 2001. Novel Bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Trans. Med. Imag. 20 (August), 772-783; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of a-stable probability densities using finite Gaussian mixtures. In: Proc. EUSIPCO'98 (September); Portilla, J., Strela, V., Wainwright, M.J., Simoncelli, E.P., 2003. Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE. Trans. Image. Proc. 12 (November), 1338-1351]. Essentially, B-F purport to propose an algorithm for image denoising based on scale mixtures of Gaussians in the wavelet domain, an approach well documented in [Portilla, J., Strela, V., Wainwright, M.J., Simoncelli, E.P., 2003. Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE. Trans. Image. Proc. 12 (November), 1338-1351]. In achieving this, B-F make use of a known method for approximating alpha-stable distributions previously proposed by Kuruoglu and co-workers [Kuruoglu, E.E., 1998. Signal processing in alpha-stable noise environments:Aleast lp-norm approach. Ph.D. thesis, University of Cambridge, Cambridge; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of alpha-stable probability densities using finite Gaussian mixtures. In: Proc. USIPCO'98 (September)], but without referring to their work. Together, the above observations do not entitle B-F to claim to have developed a new algorithm. In addition, we show that B-F [2006; Fadili, J.M., Boubchir, L., 2005. Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities. IEEE Trans. Image Process. 14 (2), 231-240] include unfair comments and comparison vis-a`-vis of the method proposed in our early work [Achim, A., Bezerianos, A., Tsakalides, P., 2001. Novel Bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Trans. Med. Imag. (August) 20, 772-783]. (literal)
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