Comments on "A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-stable prior"

Alin Achim, Ercan Kuruoglu, Anastasios Bezerianos, Panagiotis Tsakalides

Research output: Contribution to journalArticle

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 closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-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 α-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 α-stable distributions previously proposed by Kuruoglu and co-workers [Kuruoglu, E.E., 1998. Signal processing in α-stable noise environments: A least l p-norm approach. Ph.D. thesis, University of Cambridge, Cambridge; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of α-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-à-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].

Original languageEnglish (US)
Pages (from-to)1845-1847
Number of pages3
JournalPattern Recognition Letters
Volume28
Issue number13
DOIs
StatePublished - Oct 1 2007
Externally publishedYes

Fingerprint

Image denoising
Speckle
Ultrasonics
Signal processing

Keywords

  • Alpha-stable distributions
  • Bayesian estimation
  • Image denoising
  • Wavelet transform

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Comments on "A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-stable prior". / Achim, Alin; Kuruoglu, Ercan; Bezerianos, Anastasios; Tsakalides, Panagiotis.

In: Pattern Recognition Letters, Vol. 28, No. 13, 01.10.2007, p. 1845-1847.

Research output: Contribution to journalArticle

Achim, Alin ; Kuruoglu, Ercan ; Bezerianos, Anastasios ; Tsakalides, Panagiotis. / Comments on "A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-stable prior". In: Pattern Recognition Letters. 2007 ; Vol. 28, No. 13. pp. 1845-1847.
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AU - Achim, Alin

AU - Kuruoglu, Ercan

AU - Bezerianos, Anastasios

AU - Tsakalides, Panagiotis

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N2 - 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 closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-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 α-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 α-stable distributions previously proposed by Kuruoglu and co-workers [Kuruoglu, E.E., 1998. Signal processing in α-stable noise environments: A least l p-norm approach. Ph.D. thesis, University of Cambridge, Cambridge; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of α-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-à-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].

AB - 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 closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-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 α-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 α-stable distributions previously proposed by Kuruoglu and co-workers [Kuruoglu, E.E., 1998. Signal processing in α-stable noise environments: A least l p-norm approach. Ph.D. thesis, University of Cambridge, Cambridge; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of α-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-à-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].

KW - Alpha-stable distributions

KW - Bayesian estimation

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KW - Wavelet transform

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