메뉴 건너뛰기




Volumn 2, Issue , 1996, Pages 849-853

A multiresolution em algorithm for unsupervised image classification

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE CLASSIFICATION; MARKOV PROCESSES; PATTERN RECOGNITION;

EID: 33845592690     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.1996.547196     Document Type: Conference Paper
Times cited : (4)

References (13)
  • 1
    • 0000353178 scopus 로고
    • A maximization technique occuring in the statistical analysis of probabilistic functions of markov chains
    • L. E. BAUM and T.PETRIE and G. SOULES and N. WEISS. A maximization technique occuring in the statistical analysis of probabilistic functions of markov chains. Ann. Math. Stat., Vol 41: pp. 164-171, 1970.
    • (1970) Ann. Math. Stat. , vol.41 , pp. 164-171
    • Baum, L.E.1    Petrie, T.2    Soules, G.3    Weiss, N.4
  • 2
    • 0006450816 scopus 로고
    • Parameter estimation in Hidden Markov Chains and segmentation of images, (in French)
    • B. BENMILOUD and W. PIECZYNSKI. Parameter Estimation in Hidden Markov Chains and Segmentation of Images, (in french) Traitement du Signal, Vol. 12, No 5: pages 433-454, 1995.
    • (1995) Traitement du Signal , vol.12 , Issue.5 , pp. 433-454
    • Benmiloud, B.1    Pieczynski, W.2
  • 3
    • 0028392841 scopus 로고
    • A multiscale random field model for bayesian image segmentation
    • March
    • C. BOUMAN and M. SHAPIRO. A multiscale random field model for bayesian image segmentation. IEEE Trans, on Image Processing, Vol. 3, No. 2 : pages 162-177, March 1994.
    • (1994) IEEE Trans, on Image Processing , vol.3 , Issue.2 , pp. 162-177
    • Bouman, C.1    Shapiro, M.2
  • 5
    • 0024855884 scopus 로고
    • An iterative Gibbsian technique for reconstruction of m-ary images
    • B. CHALMOND. An iterative Gibbsian technique for reconstruction of m-ary images. Pattern Recognition, Vol. 22, No 6: pages 747-761, 1989.
    • (1989) Pattern Recognition , vol.22 , Issue.6 , pp. 747-761
    • Chalmond, B.1
  • 6
    • 84898819104 scopus 로고
    • Image segmentation using causal markov random fields models
    • Atlantic City, June
    • P.A. DEVIJVER. Image segmentation using causal markov random fields models. In Int. Conf. Pattern Ree, pages 153-158, Atlantic City, June 1990.
    • (1990) Int. Conf. Pattern Ree , pp. 153-158
    • Devijver, P.A.1
  • 7
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions and the bayesian restoration of images
    • November
    • S. GEMAN and D. GEMAN. Stochastic relaxation, Gibbs distributions and the bayesian restoration of images. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 6, No 6: pp. 721-741, November 1984.
    • (1984) IEEE Trans. on Pattern Analysis and Machine Intelligence , vol.6 , Issue.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 8
    • 0029225216 scopus 로고
    • Hierarchical statistical models for the fusion of multiresolution image data
    • Cambridge, USA
    • J.-M. LAFERTÉ, F. HEITZ, P. PEREZ, and E. FABRE. Hierarchical statistical models for the fusion of multiresolution image data. In Proc. Int. Conf. on Computer Vision, pages 908-913, Cambridge, USA, 1995.
    • (1995) Proc. Int. Conf. on Computer Vision , pp. 908-913
    • Laferté, J.-M.1    Heitz, F.2    Perez, P.3    Fabre, E.4
  • 9
    • 0002629270 scopus 로고
    • Mixtures densities, maximum likelihood from incomplete data via the em algorithm
    • N. M. LAIRD A. P. DEMSTER and D. B. RUBIN. Mixtures densities, maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Stat. Society, Vol. 39, No 1: pages 1-38, 1977.
    • (1977) Journal of the Royal Stat. Society , vol.39 , Issue.1 , pp. 1-38
    • Laird, N.M.1    Demster, A.P.2    Rubin, D.B.3
  • 10
    • 0027874674 scopus 로고
    • Multiscale representations of Markov random fields
    • Dec.
    • M. LUETTGEN, W. KARL, A. WILLSKY, and R. TENNEY. Multiscale representations of Markov Random Fields. IEEE Trans. Signal Processing, Vol. 41, No 12: pages 3377-3395, Dec. 1993.
    • (1993) IEEE Trans. Signal Processing , vol.41 , Issue.12 , pp. 3377-3395
    • Luettgen, M.1    Karl, W.2    Willsky, A.3    Tenney, R.4
  • 11
    • 0021404166 scopus 로고
    • Mixtures densities, maximum likelihood and the em algorithm
    • April
    • R. A. REDNER and H. F. WALKER. Mixtures densities, maximum likelihood and the EM algorithm. SIAM Review, Vol. 26, No 2: pages 195-239, April 1984.
    • (1984) SIAM Review , vol.26 , Issue.2 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 12
    • 84950432017 scopus 로고
    • A Monte-Carlo implementation of the em algorithm and the poor man's data augmentation algorithms
    • G.C.G. WEI and M.A. TANNER. A Monte-Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms. Journal of the American Statistical Association, 85: pages 699-704, 1990.
    • (1990) Journal of the American Statistical Association , vol.85 , pp. 699-704
    • Wei, G.C.G.1    Tanner, M.A.2
  • 13
    • 0028466714 scopus 로고
    • Maximum-likelihood parameter estimation for unsupervised stochastic model-based image segmentation
    • July
    • J. ZHANG, J. W. MODESTINO, and D. A. LANG AN. Maximum-likelihood parameter estimation for unsupervised stochastic model-based image segmentation. IEEE Trans, on Image Processing, Vol. 3, No 4: pages 404-420, July 1994.
    • (1994) IEEE Trans, on Image Processing , vol.3 , Issue.4 , pp. 404-420
    • Zhang, J.1    Modestino, J.W.2    Lang An, D.A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.