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Cited by 80Advanced Image Processing TechniquesImage and Signal Denoising MethodsImage Processing Techniques and Applications

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student's-t Priors

Tzikas, D.G., Likas, A.C., Galatsanos, N.P.·2009·IEEE Transactions on Image Processing
DOI 10.1109/tip.2008.2011757
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Abstract

In this paper, we present a new Bayesian model for the blind image deconvolution (BID) problem. The main novelty of this model is the use of a sparse kernel-based model for the point spread function (PSF) that allows estimation of both PSF shape and support. In the herein proposed approach, a robust model of the BID errors and an image prior that preserves edges of the reconstructed image are also used. Sparseness, robustness, and preservation of edges are achieved by using priors that are based on the Student's-t probability density function (PDF). This pdf, in addition to having heavy tails, is closely related to the Gaussian and, thus, yields tractable inference algorithms. The approximate variational inference methodology is used to solve the corresponding Bayesian model. Numerical experiments are presented that compare this BID methodology to previous ones using both simulated and real data.

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Research works printed but not linked: 26

  1. 10.1109/TIP.2005.847322 · DOI
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  22. liu, 1995, ml estimation of the t distribution using em and its extensions, ecm and ecme, Statist Sin, 5, 19
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Metadata

Authors
Tzikas, D. G., Likas, A. C., & Galatsanos, N. P.
Affiliations
  • University of Ioannina (GR)
  • University of Patras (GR)
ORCID
Likas, A.C.
Venue
IEEE Transactions on Image Processing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2009-04
Volume
18
Issue
4
Pages
753-764
ISSN
1057-7149 (ISSN-L)
DOI
10.1109/tip.2008.2011757
OpenAlex
W2128104012
Cited by
80
References
2
Citations by year
2026: 1 · 2025: 4 · 2024: 1 · 2022: 5 · 2020: 3 · 2019: 2 · 2018: 3 · 2017: 6 · 2016: 6 · 2015: 9 · 2014: 12 · 2013: 8 · 2012: 8
FWCI
7.35
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
  • IEEE Transactions on Image Processing (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image Processing Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
  • Physical Sciences › Engineering › Media Technology › Image Processing Techniques and Applications
Keywords
blind image deconvolution, sparse kernels, point spread function estimation, heavy-tailed priors, variational inference, edge preservation, sparse priors

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CoChat. (2026). Citation check: Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student's-t Priors. https://app.cochat.ai/papers/10.1109/tip.2008.2011757
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Tzikas, D. G., Likas, A. C., & Galatsanos, N. P. (2009). Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student's-t Priors. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2008.2011757