Title :
A Bayesian wavelet-based multidimensional deconvolution with sub-band emphasis
Author :
Zhang, Yingsong ; Kingsbury, Nick
Author_Institution :
Signal Processing & Communication Group, Dept. of Engineering, University of Cambridge, CB2 1PZ, UK
Abstract :
This work proposes a new algorithm for wavelet-based multidimensional image deconvolution which employs subband-dependent minimization and the dual-tree complex wavelet transform in an iterative Bayesian framework. In addition, this algorithm employs a new prior instead of the popular ℓ1 norm, and is thus able to embed a learning scheme during the iteration which helps it to achieve better deconvolution results and faster convergence.
Keywords :
Bayesian methods; Continuous wavelet transforms; Deconvolution; Iterative algorithms; Multidimensional signal processing; Multidimensional systems; Nonlinear filters; Signal processing algorithms; Wavelet domain; Wavelet transforms; Algorithms; Bayes Theorem; Computer Simulation; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Models, Statistical; Models, Theoretical; Normal Distribution; Numerical Analysis, Computer-Assisted; Reproducibility of Results; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4649840
