- Research Article
- Open access
- Published:
An Adaptively Accelerated Bayesian Deblurring Method with Entropy Prior
EURASIP Journal on Advances in Signal Processing volume 2008, Article number: 674038 (2008)
Abstract
The development of an efficient adaptively accelerated iterative deblurring algorithm based on Bayesian statistical concept has been reported. Entropy of an image has been used as a "prior" distribution and instead of additive form, used in conventional acceleration methods an exponent form of relaxation constant has been used for acceleration. Thus the proposed method is called hereafter as adaptively accelerated maximum a posteriori with entropy prior (AAMAPE). Based on empirical observations in different experiments, the exponent is computed adaptively using first-order derivatives of the deblurred image from previous two iterations. This exponent improves speed of the AAMAPE method in early stages and ensures stability at later stages of iteration. In AAMAPE method, we also consider the constraint of the nonnegativity and flux conservation. The paper discusses the fundamental idea of the Bayesian image deblurring with the use of entropy as prior, and the analytical analysis of superresolution and the noise amplification characteristics of the proposed method. The experimental results show that the proposed AAMAPE method gives lower RMSE and higher SNR in 44% lesser iterations as compared to nonaccelerated maximum a posteriori with entropy prior (MAPE) method. Moreover, AAMAPE followed by wavelet wiener filtering gives better result than the state-of-the-art methods.
Publisher note
To access the full article, please see PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Singh, M.K., Tiwary, U.S. & Kim, YH. An Adaptively Accelerated Bayesian Deblurring Method with Entropy Prior. EURASIP J. Adv. Signal Process. 2008, 674038 (2008). https://doi.org/10.1155/2008/674038
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1155/2008/674038