Image processing, image analysis, Markov random fields, and MCMC

 

S. Geman and D. Geman. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE-PAMI, 6, 1984, 721-741.

(pdf)

 

S. Geman and D.E. McClure. Bayesian image analysis: An application to single photon emission tomography. 1985 Proceedings of the American Statistical Association. Statistical Computing Section, 1985, 12-18. (pdf)

 

S. Geman and C.-R. Hwang. Diffusions for global optimization. SIAM J. Control and Optimization, 24, 1986, 1031-1043. (pdf)

 

D. Geman and S. Geman. Bayesian image analysis. Disordered Systems and Biological Organization. Ed. E. Bienenstock, F. Fogelman, G. Weisbuch. NATO ASI Series, Vol. F20, Springer-Verlag , Berlin , 1986. (pdf)

 

D. Geman, S. Geman, and C. Graffigne. Locating texture and object boundaries. Pattern Recognition Theory and Application. Ed. P. Devijver. NATO ASI Series, Springer-Verlag, Heidelberg, 1986. (pdf)

 

S. Geman and D.E. McClure. Discussion of: "On the statistical analysis of dirty pictures," by Julian Besag, J. R. Statist. Soc. B, 48, 1986, 259-302.

 

S. Geman and C. Graffigne. Markov random field image models and their applications to computer vision. Proceedings of the International Congress of Mathematicians 1986. Ed. A.M. Gleason, American Mathematical Society, Providence , 1987. (pdf)

 

S. Geman and D.E. McClure. Statistical methods for tomographic image reconstruction. Proceedings of the 46th Session of the International Statistical Institute, Bulletin of the ISI, 52, 1987. (pdf)

 

S. Geman. Experiments in Bayesian Image Analysis. Bayesian Statistics 3. Ed. J.M. Bernardo, M.H. DeGroot, D.V. Lindley and A.F.M. Smith, Oxford University Press, 1988. (pdf)

 

S. Geman. Stochastic relaxation methods for image restoration and expert systems. Maximum Entropy and Bayesian Methods in Science and Engineering (Vol. 2). Ed. G.J.

Erickson and C.R. Smith, Kluwer Academic Publishers, 1988.

 

D. Geman, S. Geman, C. Graffigne, and P. Dong. Boundary detection by constrained optimization. IEEE-PAMI, 12, 1990, 609-628. (pdf)

 

D. Geman and S. Geman. Discussion of: "Bayesian image restoration, with two applications in spatial statistics," by J.E. Besag, Jeremy York and Annie Mollié, Annals of the Institute of Statistical Mathematics, 43, 1991.

 

S. Geman, D.E. McClure, and D. Geman. A nonlinear filter for film restoration and other problems in image processing. CVGIP: Graphical and Image Processing, 54, 1992, 281-289. (pdf)

 

S. Geman, K. Manbeck, and D.E. McClure. A comprehensive statistical model for single photon emission tomography. In: Markov Random Fields: Theory and Applications. Eds. R. Chellappa and A. Jain. Academic Press, Boston, 1993, 93-130. (pdf)

 

S. Geman, K. Manbeck, and D.E. McClure. "Coarse-to-fine search and rank-sum statistics in object recognition." Technical Report, Division of Applied Mathematics, Brown University, 1995. (pdf)

 

H. Künsch, S. Geman, and A. Kehagias. Hidden Markov random fields. Annals of Applied Probability, 5, 1995, 577-602. (pdf)

(complete proofs can be found in this ``appendix" pdf)

 

L.-B. Chang, Y. Jin, W. Zhang, E. Borenstein, and S. Geman. Context, Computation, and Optimal ROC Performance in Hierarchical Models. IJCV, 93(2), 2011, 117-140. (pdf)

T.-L. Chen and S. Geman. Image Warping Using Radial Basis Functions. J. of Applied Statistics, 42(2), 2014, 242-258. (pdf)

L.-B. Chang, E. Borenstein, W. Zhang, and S. Geman. Maximum likelihood features for generative image models. Annals of Applied Statistics, vol. 11(3), 2017, 1275-1308. (pdf)