We develop a novel multivariate Bayesian wavelet estimator of a simple analytical form that is computationally effective for the image denoising problem. The estimator is derived from the multivariate Laplacian model by using the maximum a posteriori rule. We find the multivariate estimator produces restoration results of high quality, both visually and in terms of peak signal-to-noise ratio.
© 2007 Optical Society of America
Original Manuscript: April 30, 2007
Revised Manuscript: July 10, 2007
Manuscript Accepted: July 26, 2007
Published: August 22, 2007
Shan Tan and Licheng Jiao, "Multishrinkage: analytical form for a Bayesian wavelet estimator based on the multivariate Laplacian model," Opt. Lett. 32, 2583-2585 (2007)