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Volumn 15, Issue , 2011, Pages 883-891

Dependent hierarchical beta process for image interpolation and denoising

Author keywords

[No Author keywords available]

Indexed keywords

BERNOULLI PROCESS; COVARIATES; DE-NOISING; IMAGE INTERPOLATIONS; IMAGE PATCHES; NOISE MODELS; SPARSE SET; STATE-OF-THE-ART PERFORMANCE; TRAINING DATA; WHITE GAUSSIAN NOISE;

EID: 84862283539     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (37)

References (25)
  • 1
    • 33750383209 scopus 로고    scopus 로고
    • The KSVD: An algorithm for designing of overcomplete dictionaries for sparse representations
    • M. Aharon, M. Elad, and A. M. Bruckstein. The KSVD: An algorithm for designing of overcomplete dictionaries for sparse representations. IEEE Trans. Signal Process., 2006.
    • (2006) IEEE Trans. Signal Process
    • Aharon, M.1    Elad, M.2    Bruckstein, A.M.3
  • 3
    • 79960675858 scopus 로고    scopus 로고
    • Robust principal component analysis?
    • accepted for publication in
    • E. J. Candès, X. Li, Y. Ma, and J. Wright. Robust principal component analysis? accepted for publication in Journal of the ACM, 2011.
    • (2011) Journal of the ACM
    • Candès, E.J.1    Li, X.2    Ma, Y.3    Wright, J.4
  • 5
    • 33947142837 scopus 로고    scopus 로고
    • Theoretical results on sparse representations of multiple-measurement vectors
    • J. Chen and X. Huo. Theoretical results on sparse representations of multiple-measurement vectors. IEEE Trans. Sigal Process, 2006.
    • (2006) IEEE Trans. Sigal Process
    • Chen, J.1    Huo, X.2
  • 8
    • 33751379736 scopus 로고    scopus 로고
    • Image denoising via sparse and redundant representations over learned dictionaries
    • M. Elad and M. Aharon. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. Image Process., 2006.
    • (2006) IEEE Trans. Image Process
    • Elad, M.1    Aharon, M.2
  • 10
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov chains and their application
    • W. Hastings. Monte Carlo sampling methods using Markov chains and their application. Biometrika, 1970.
    • (1970) Biometrika
    • Hastings, W.1
  • 15
    • 53149111169 scopus 로고    scopus 로고
    • Reduce and boost: Recovering arbitrary sets of jointly sparse vectors
    • M. Mishali and Y. C. Eldar. Reduce and boost: Recovering arbitrary sets of jointly sparse vectors. IEEE Trans. Sigal Process., 2008.
    • (2008) IEEE Trans. Sigal Process
    • Mishali, M.1    Eldar, Y.C.2
  • 20
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • J. B. Tenenbaum, V. Silva, and J. C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 2000.
    • (2000) Science
    • Tenenbaum, J.B.1    Silva, V.2    Langford, J.C.3
  • 22
    • 30844461481 scopus 로고    scopus 로고
    • Algorithms for simultaneous sparse approximation. part II: Convex relaxation
    • J. Tropp. Algorithms for simultaneous sparse approximation. part II: Convex relaxation. Signal Process., 2006.
    • (2006) Signal Process
    • Tropp, J.1
  • 24
    • 84863367863 scopus 로고    scopus 로고
    • Robust principal component analysis: Exact recovery of corrupted low-rank matrices by convex optimization
    • J. Wright, Y. Peng, Y. Ma, A. Ganesh, and S. Rao. Robust principal component analysis: Exact recovery of corrupted low-rank matrices by convex optimization. In Proc. Neural Information Processing Systems, 2009.
    • (2009) Proc. Neural Information Processing Systems
    • Wright, J.1    Peng, Y.2    Ma, Y.3    Ganesh, A.4    Rao, S.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.