메뉴 건너뛰기




Volumn 24, Issue 4, 2007, Pages 973-983

Approach to blind image deconvolution by multiscale subband decomposition and independent component analysis

Author keywords

[No Author keywords available]

Indexed keywords

BLIND SOURCE SEPARATION; DECONVOLUTION; INDEPENDENT COMPONENT ANALYSIS; WAVELET DECOMPOSITION;

EID: 34248356039     PISSN: 10847529     EISSN: None     Source Type: Journal    
DOI: 10.1364/JOSAA.24.000973     Document Type: Article
Times cited : (17)

References (42)
  • 3
    • 0002594849 scopus 로고
    • Bayesian-based iterative method of image restoration
    • W. H. Richardson, "Bayesian-based iterative method of image restoration," J. Opt. Soc. Am. 62, 55-59 (1972).
    • (1972) J. Opt. Soc. Am , vol.62 , pp. 55-59
    • Richardson, W.H.1
  • 4
    • 0001050714 scopus 로고
    • An iterative technique for rectification of observed distribution
    • L. B. Lucy, "An iterative technique for rectification of observed distribution," Astron. J. 79, 745-754 (1974).
    • (1974) Astron. J , vol.79 , pp. 745-754
    • Lucy, L.B.1
  • 5
  • 6
    • 0005249987 scopus 로고    scopus 로고
    • Acceleration of iterative image restoration algorithms
    • D. S. C. Biggs and M. Andrews, "Acceleration of iterative image restoration algorithms," Appl. Opt. 36, 1766-1775 (1997).
    • (1997) Appl. Opt , vol.36 , pp. 1766-1775
    • Biggs, D.S.C.1    Andrews, M.2
  • 10
    • 1242309785 scopus 로고    scopus 로고
    • Independent component analysis approach to image sharpening in the presence of atmospheric turbulence
    • I. Kopriva, Q. Du, H. Szu, and W. Wasylkiwskyj, "Independent component analysis approach to image sharpening in the presence of atmospheric turbulence," Opt. Commun. 233, 7-14 (2004).
    • (2004) Opt. Commun , vol.233 , pp. 7-14
    • Kopriva, I.1    Du, Q.2    Szu, H.3    Wasylkiwskyj, W.4
  • 12
    • 0024053929 scopus 로고
    • Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression
    • J. G. Daugman, "Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression," IEEE Trans. Acoust., Speech, Signal Process. 36, 1169-1179 (1988).
    • (1988) IEEE Trans. Acoust., Speech, Signal Process , vol.36 , pp. 1169-1179
    • Daugman, J.G.1
  • 14
    • 29444451047 scopus 로고    scopus 로고
    • Single-frame multichannel blind deconvolution by nonnegative matrix factorization with sparseness constraints
    • I. Kopriva, "Single-frame multichannel blind deconvolution by nonnegative matrix factorization with sparseness constraints," Opt. Lett. 30, 3135-3137 (2005).
    • (2005) Opt. Lett , vol.30 , pp. 3135-3137
    • Kopriva, I.1
  • 15
    • 33745725481 scopus 로고    scopus 로고
    • Non-negative matrix factorization approach to blind image deconvolution
    • I. Kopriva and D. Nuzillard, "Non-negative matrix factorization approach to blind image deconvolution," Lect. Notes Comput. Sci. 3889, 966-973 (2006).
    • (2006) Lect. Notes Comput. Sci , vol.3889 , pp. 966-973
    • Kopriva, I.1    Nuzillard, D.2
  • 16
    • 33748956840 scopus 로고    scopus 로고
    • Single frame blind image deconvolution by non-negative sparse matrix factorization
    • I. Kopriva, D. J. Garrood, and V. Borjanović, "Single frame blind image deconvolution by non-negative sparse matrix factorization," Opt. Commun. 266, 456-464 (2006).
    • (2006) Opt. Commun , vol.266 , pp. 456-464
    • Kopriva, I.1    Garrood, D.J.2    Borjanović, V.3
  • 18
    • 0038713119 scopus 로고    scopus 로고
    • Blind source separation algorithms with matrix constraints
    • A. Cichocki and P. Georgiev, "Blind source separation algorithms with matrix constraints," IEICE Trans. Fundamentals E86-A, 522-531 (2003).
    • (2003) IEICE Trans. Fundamentals , vol.E86-A , pp. 522-531
    • Cichocki, A.1    Georgiev, P.2
  • 20
    • 33645721350 scopus 로고    scopus 로고
    • An adaptive method for subband decomposition ICA
    • K. Zhang and L. W. Chan, "An adaptive method for subband decomposition ICA," Neural Comput. 18, 191-223 (2006).
    • (2006) Neural Comput , vol.18 , pp. 191-223
    • Zhang, K.1    Chan, L.W.2
  • 21
    • 33745697451 scopus 로고    scopus 로고
    • Enhancement of source independence for blind source separation
    • K. Zhang and L. W. Chan, "Enhancement of source independence for blind source separation," Lect. Notes Comput. Sci. 3889, 731-738 (2006).
    • (2006) Lect. Notes Comput. Sci , vol.3889 , pp. 731-738
    • Zhang, K.1    Chan, L.W.2
  • 24
    • 0031675604 scopus 로고    scopus 로고
    • Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
    • C. L. Bryne, "Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods," IEEE Trans. Image Process. 7, 100-109 (1998).
    • (1998) IEEE Trans. Image Process , vol.7 , pp. 100-109
    • Bryne, C.L.1
  • 31
    • 2442473143 scopus 로고    scopus 로고
    • Analysis of sparse representation and blind source separation
    • Y. Li, A. Cichocki, and S. Amari, "Analysis of sparse representation and blind source separation," Neural Comput. 16, 1193-1234 (2004).
    • (2004) Neural Comput , vol.16 , pp. 1193-1234
    • Li, Y.1    Cichocki, A.2    Amari, S.3
  • 32
    • 23044451368 scopus 로고    scopus 로고
    • Sparse component analysis and blind source separation of underdetermined mixtures
    • P. Georgiev, F. Theis, and A. Cichocki, "Sparse component analysis and blind source separation of underdetermined mixtures," IEEE Trans. Neural Netw. 16, 992-996 (2005).
    • (2005) IEEE Trans. Neural Netw , vol.16 , pp. 992-996
    • Georgiev, P.1    Theis, F.2    Cichocki, A.3
  • 33
    • 31344466301 scopus 로고    scopus 로고
    • Underdetermined blind source separation based on sparse representation
    • Y. Li, S. Amari, A. Cichocki, D. W. C. Ho, and S. Xie, "Underdetermined blind source separation based on sparse representation," IEEE Trans. Signal Process. 54, 423-437 (2006).
    • (2006) IEEE Trans. Signal Process , vol.54 , pp. 423-437
    • Li, Y.1    Amari, S.2    Cichocki, A.3    Ho, D.W.C.4    Xie, S.5
  • 34
    • 8344255793 scopus 로고    scopus 로고
    • Multiscale framework for blind separation of linearly mixed signals
    • P. Kisilev, M. Zibulevsky, and Y. Y. Zeevi, "Multiscale framework for blind separation of linearly mixed signals," J. Mach. Learn. Res. 4, 1339-1363 (2003).
    • (2003) J. Mach. Learn. Res , vol.4 , pp. 1339-1363
    • Kisilev, P.1    Zibulevsky, M.2    Zeevi, Y.Y.3
  • 35
    • 8344285779 scopus 로고    scopus 로고
    • Dependence, correlation and Gaussianity in independent component analysis
    • J. F. Cardoso, "Dependence, correlation and Gaussianity in independent component analysis," J. Mach. Learn. Res. 4, 1177-1203 (2003).
    • (2003) J. Mach. Learn. Res , vol.4 , pp. 1177-1203
    • Cardoso, J.F.1
  • 38
    • 0028416938 scopus 로고
    • Independent component analysis, a new concept?
    • R. Comon, "Independent component analysis, a new concept?" Signal Process. 36, 287-314 (1994).
    • (1994) Signal Process , vol.36 , pp. 287-314
    • Comon, R.1
  • 40
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • P. O. Hoyer, "Non-negative matrix factorization with sparseness constraints," J. Mach. Learn. Res. 5, 1457-1469 (2004).
    • (2004) J. Mach. Learn. Res , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 41
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization," Nature 401, 788-791 (1999).
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 42
    • 33745683306 scopus 로고    scopus 로고
    • Csiszár's divergences for non-negative matrix factorization: Family of new algorithms
    • A. Cichocki, R. Zdunek, and S. Amari, "Csiszár's divergences for non-negative matrix factorization: family of new algorithms," Lect. Notes Comput. Sci. 3889, 32-39 (2006).
    • (2006) Lect. Notes Comput. Sci , vol.3889 , pp. 32-39
    • Cichocki, A.1    Zdunek, R.2    Amari, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.