메뉴 건너뛰기




Volumn , Issue , 2007, Pages 181-186

Hyperparameter estimation in Bayesian image superresolution with a compound markov random field prior

Author keywords

[No Author keywords available]

Indexed keywords

ARSENIC COMPOUNDS; ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; CANNING; CHLORINE COMPOUNDS; ESTIMATION; FACILITIES; HIDDEN MARKOV MODELS; IMAGE ACQUISITION; IMAGE REGISTRATION; IMAGE SEGMENTATION; LEARNING SYSTEMS; MARKOV PROCESSES; OPTICAL RESOLVING POWER; RANDOM PROCESSES; ROBOT LEARNING; SEISMIC PROSPECTING; SIGNAL PROCESSING; STRUCTURAL FRAMES;

EID: 48149106955     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2007.4414303     Document Type: Conference Paper
Times cited : (7)

References (15)
  • 2
    • 85032751363 scopus 로고    scopus 로고
    • Super-resolution image reconstruction: A technical overview
    • S. C. Park, M. K. Park, and M. G. Kang, "Super-resolution image reconstruction: A technical overview," IEEE Signal Process. Mag., vol. 20, no. 3, pp. 21-36, 2003.
    • (2003) IEEE Signal Process. Mag , vol.20 , Issue.3 , pp. 21-36
    • Park, S.C.1    Park, M.K.2    Kang, M.G.3
  • 4
    • 0004170773 scopus 로고    scopus 로고
    • Spatial resolution enhancement of low-resolution image sequences: A comprehensive review with directions for future research,
    • Tech. Rep, Univ. of Notre Dame
    • S. Borman and R. L. Stevenson, "Spatial resolution enhancement of low-resolution image sequences: A comprehensive review with directions for future research," Tech. Rep., Univ. of Notre Dame, 1998.
    • (1998)
    • Borman, S.1    Stevenson, R.L.2
  • 5
    • 0026898364 scopus 로고
    • Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation
    • N. P. Galatsanos and A. K. Katsaggelos, "Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation," IEEE Trans. Image Process., vol. 1, no. 3, pp. 322-336, 1992.
    • (1992) IEEE Trans. Image Process , vol.1 , Issue.3 , pp. 322-336
    • Galatsanos, N.P.1    Katsaggelos, A.K.2
  • 6
    • 0033078391 scopus 로고    scopus 로고
    • Bayesian and regularization methods for hyperparameter estimation in image restoration
    • R. Molina, A. K. Katsaggelos, and J. Mateos, "Bayesian and regularization methods for hyperparameter estimation in image restoration," IEEE Trans. Image Process., vol. 8, no. 2, pp. 231-246, 1999.
    • (1999) IEEE Trans. Image Process , vol.8 , Issue.2 , pp. 231-246
    • Molina, R.1    Katsaggelos, A.K.2    Mateos, J.3
  • 7
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • D. J. C. MacKay, "Bayesian interpolation," Neural Computation, vol. 4, no. 3, pp. 415-447, 1992.
    • (1992) Neural Computation , vol.4 , Issue.3 , pp. 415-447
    • MacKay, D.J.C.1
  • 8
    • 84898940249 scopus 로고    scopus 로고
    • Bayesian image super-resolution,
    • MIT Press
    • M. E. Tipping and C. M. Bishop, "Bayesian image super-resolution, " in Advances in NIPS 15. 2003, pp. 1279-1286, MIT Press.
    • (2003) Advances in NIPS 15 , pp. 1279-1286
    • Tipping, M.E.1    Bishop, C.M.2
  • 10
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
    • S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal Mach. Intell., vol. PAMI-6, no. 6, pp. 721-741, 1984.
    • (1984) IEEE Trans. Pattern Anal Mach. Intell , vol.PAMI-6 , Issue.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 11
    • 0026124056 scopus 로고
    • Compound Gauss-Markov random fields for image estimation
    • F.-C. Jeng and J. W. Woods, "Compound Gauss-Markov random fields for image estimation," IEEE Trans. Signal Process., vol. 39, no. 3, pp. 683-697, 1991.
    • (1991) IEEE Trans. Signal Process , vol.39 , Issue.3 , pp. 683-697
    • Jeng, F.-C.1    Woods, J.W.2
  • 12
    • 10344237188 scopus 로고    scopus 로고
    • Bayesian multichannel image restoration using compound Gauss-Markov random fields
    • R. Molina, J. Mateos, A. K. Katsaggelos, and M. Vega, "Bayesian multichannel image restoration using compound Gauss-Markov random fields," IEEE Trans. Image Process., vol. 12, no. 12, pp. 1642-1654, 2003.
    • (2003) IEEE Trans. Image Process , vol.12 , Issue.12 , pp. 1642-1654
    • Molina, R.1    Mateos, J.2    Katsaggelos, A.K.3    Vega, M.4
  • 14
    • 0002788893 scopus 로고    scopus 로고
    • A view of the EM algorithm that justifies incremental, sparse, and other variants
    • Michael I. Jordan, Ed. Kluwer Academic Press
    • R. M. Neal and G. E. Hinton, "A view of the EM algorithm that justifies incremental, sparse, and other variants," in Learning in Graphical Models, Michael I. Jordan, Ed. Kluwer Academic Press, 1998.
    • (1998) Learning in Graphical Models
    • Neal, R.M.1    Hinton, G.E.2
  • 15
    • 0003278032 scopus 로고    scopus 로고
    • Inferring parameters and structure of latent variable models by variational Bayes
    • San Francisco, CA, Morgan Kaufmann
    • H. Attias, "Inferring parameters and structure of latent variable models by variational Bayes," in Proc. UAI, San Francisco, CA, 1999, pp. 21-30, Morgan Kaufmann.
    • (1999) Proc. UAI , pp. 21-30
    • Attias, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.