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W. Qian, D.M. Titterington, "Bayesian Image Restoration: An Application to EdgePreserving Surface Recovery," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 7, pp. 748752, July, 1993.  
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@article{ 10.1109/34.221174, author = {W. Qian and D.M. Titterington}, title = {Bayesian Image Restoration: An Application to EdgePreserving Surface Recovery}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {15}, number = {7}, issn = {01628828}, year = {1993}, pages = {748752}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.221174}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Bayesian Image Restoration: An Application to EdgePreserving Surface Recovery IS  7 SN  01628828 SP748 EP752 EPD  748752 A1  W. Qian, A1  D.M. Titterington, PY  1993 KW  Bayesian image restoration; image processing; 2D surface recovery; parameter estimation; parametric methods; edgepreserving surface recovery; textural image; Markov random field; nonparametric methods; Bayes methods; image reconstruction; image texture; iterative methods; Markov processes; parameter estimation VL  15 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
Bayesian methods for recovering a 2D surface are discussed. It is assumed that there is a textural image that can be modeled by a Markov random field and that the original surface is composed of different surfaces, each of which is associated with one textural state. Both parametric and nonparametric methods are used to enforce smoothness of these surfaces. Iterative procedures are examined for simultaneous restoration of the textural image and estimation of underlying parameters. From the estimated textural image and the estimated parameters, an estimate for the original surface is obtained. Two illustrative examples are presented.
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