Fast communication: The BKF Bayesian wavelet estimator

Authors:
Saralees Nadarajah;Samuel Kotz
Affiliations:
University of Manchester, Manchester M60 1QD, UK;George Washington University, Washington, DC 20052, USA
Venue:
Signal Processing
Year:
2007

Citing 4
Cited 0

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

Pattern Recognition Letters
Wavelet-based statistical signal processing using hidden Markovmodels

IEEE Transactions on Signal Processing
Adaptive wavelet thresholding for image denoising and compression

IEEE Transactions on Image Processing
Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities

IEEE Transactions on Image Processing

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Abstract

Bayesian approach for wavelet estimation has been a popular topic. The recent papers by Boubchir and Fadili [A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior, Pattern Recognition Lett. 27 (September 2006) 1370-1382, Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities, IEEE Trans. Image Process. 14 (February 2005) 231-240] derived a Bayesian wavelet estimator when the prior for wavelet coefficients is assumed to take the Bessel K form (BKF). Actually, only an approximate formula for the wavelet estimator was derived because it was claimed that the exact analytical form of the BKF prior model was difficult to deal with. In this note, we derive the corresponding expression in its exact form and provide computer programs. The expression involves some well-known special functions.