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| V.E. Johnson, W.H. Wong, X. Hu, C.T. Chen, "Image Restoration Using Gibbs Priors: Boundary Modeling, Treatment of Blurring, and Selection of Hyperparameter," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 5, pp. 413-425, May, 1991. | |||
| BibTex | x | ||
| @article{ 10.1109/34.134041, author = {V.E. Johnson and W.H. Wong and X. Hu and C.T. Chen}, title = {Image Restoration Using Gibbs Priors: Boundary Modeling, Treatment of Blurring, and Selection of Hyperparameter}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {13}, number = {5}, issn = {0162-8828}, year = {1991}, pages = {413-425}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.134041}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Image Restoration Using Gibbs Priors: Boundary Modeling, Treatment of Blurring, and Selection of Hyperparameter IS - 5 SN - 0162-8828 SP413 EP425 EPD - 413-425 A1 - V.E. Johnson, A1 - W.H. Wong, A1 - X. Hu, A1 - C.T. Chen, PY - 1991 KW - image restoration; picture processing; hyperparameter selection; Gibbs priors; boundary modeling; blurring; Bayesian model; correlation; iterative conditional averages; blurring; masking; Bayes methods; correlation methods; iterative methods; picture processing VL - 13 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
The authors propose a Bayesian model for the restoration of images based on counts of emitted photons. The model treats blurring within the context of an incomplete data problem and utilizes a Gibbs prior to model the spatial correlation of neighboring regions. The Gibbs prior includes line sites to account for boundaries between regions, and the line sites are assigned continuous values to permit efficient estimation using a method called iterative conditional averages. In addition, the effect of blurring in masking differences between images and the effects of misspecifying the amount of blurring are discussed.
[1] J. Besag, "Spatial interaction and the statistical analysis of lattice systems,"J. Roy. Statist. Soc., series B, vol. 36, pp. 192-326, 1974.
[2] J. Besag, "On the statistical analysis of dirty pictures,"J. Roy. Statist. Soc., series B, vol. 48, pp. 259-302, 1986.
[3] S. Giesser, "The predictive sample reuse method with applications,"J. Amer. Stat. Assoc., vol. 70, pp. 320-328, 1975.
[4] D. Geman, S. Geman, C. Graffigne, and P. Dong, "Boundary detection by constrained optimization,"IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 609-628, 1990.
[5] S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 721-741, 1984.
[6] S. Geman and D. E. McClure, "Bayesian image analysis: An application to single photon emission tomography," inProc. Amer. Statist. Assoc. Statistical Computing Section, 1985, pp. 12-18.
[7] P. J. Green, "Bayesian reconstruction from emission tomography data using a modified EM algorithm,"IEEE Trans. Med. Imaging, vol. 9, pp. 84-93, 1990.
[8] V. Johnson, W. Wing, X. Hu, and C. T. Chen, "Data augmentation schemes applied to image restoration," inProc. NATO Advanced Study Inst. Formation, Handling and Evaluation of Medical Images, A. E. Todd-Pokropek and M. A. Viergever, Eds., 1988.
[9] K. Lange and R. Carson, "EM reconstruction algorithms for emission and tramsmission tomography,"J. Comput. Assisted Tomography, vol. 8, pp. 306-318, 1984.
[10] P. McCullagh and J. A. Nelder,Generalized Linear Models. New York: Chapman and Hall, 1983.
[11] A. Owen, in discussion of "Statistics, images, and pattern recognition," B. Ripley,Canadian J. Statist., vol. 14, pp. 83-111, 1986.
[12] C. R. Rao,Linear Statistical Inference and its Applications, 2nd ed. New York: Wiley, 1973, pp. 425-427.
[13] L. Shepp and Y. Vardi, "Maximum likelihood reconstruction for emission tomography,"IEEE Trans. Med. Imaging, vol. MI-1, pp. 113-122, 1982.
[14] B. W. Silverman, C. Jennison, J. Stander, and T.C. Brown, "The specification of edge penalties for regular and irregular pixel images,"IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 1017-1024, 1990.
[15] B. W. Silverman, M. C. Jones, D. W. Nychka, and J. D. Wilson, "A smoothed EM algorithm to indirect estimation problems, with particular reference to stereology and emission tomography,"J. Roy. Statist. Soc., series B, vol. 52, pp. 271-324, 1990.
[16] M. Stone, "Cross-validatory choice and assessment of statistical predictions,"J. Roy. Statist. Soc., series B, vol. 36, pp. 111-147, 1974.
[17] M. Tanner and W. H. Wong, "Calculation of posterior distributions by data augmentation,"J. Amer. Stat. Assoc., vol. 82, pp. 528-540, 1987.
[18] Y. Vardi, L. A. Shepp, and L. Kaufman, "A statistical model for positron emission tomography,"J. Amer. Stat. Assoc., vol. 80, pp. 8-25, 1985.

