PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Czasopismo
2013 | 11 | 10 | 1414-1422
Tytuł artykułu

Fractional-order TV-L2 model for image denoising

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.
Wydawca

Czasopismo
Rocznik
Tom
11
Numer
10
Strony
1414-1422
Opis fizyczny
Daty
wydano
2013-10-01
online
2013-12-19
Twórcy
autor
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China, chendali@ise.neu.edu.cn
autor
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
  • MESA Lab, University of California, Merced, 5200 North Lake Road, Merced, CA, 95343, USA
autor
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
Bibliografia
  • [1] L. Ruding, S. Osher, E. Fatemi, Physica D 60, 259 (1992) http://dx.doi.org/10.1016/0167-2789(92)90242-F[Crossref]
  • [2] J. F. Aujol, J. Math. Imaging Vis. 34, 307 (2009) http://dx.doi.org/10.1007/s10851-009-0149-y[Crossref]
  • [3] C. Vogel, M. Oman, IEEE T. Image Process. 7, 813 (1998) http://dx.doi.org/10.1109/83.679423[Crossref]
  • [4] F. Alter, S. Durand, J. Froment, J. Math. Imaging Vis. 23, 199 (2005) http://dx.doi.org/10.1007/s10851-005-6467-9[Crossref]
  • [5] F. Li, C. Shen, C. Li, J. Math. Imaging Vis. 37, 98 (2010) http://dx.doi.org/10.1007/s10851-010-0195-5[Crossref]
  • [6] J. Zhang, Z. Wei, L. Xiao, J. Math. Imaging Vis. 43, 39 (2012) http://dx.doi.org/10.1007/s10851-011-0285-z[Crossref]
  • [7] Y. L. You, M. Kaveh, IEEE T. Image Process. 9, 1723 (2000) http://dx.doi.org/10.1109/83.869184[Crossref]
  • [8] M. Hajiaboli, IPSJ Transactions on Computer Vision and Application 2, 94 (2010) http://dx.doi.org/10.2197/ipsjtcva.2.94[Crossref]
  • [9] R. Herrmann, Fractional Calculus: An Introduction for Physicists (World Scientific, New Jersey, 2011) http://dx.doi.org/10.1142/8072[Crossref]
  • [10] S. C. Liu, S. Chang, IEEE T. Image Process. 6, 1176 (1997) http://dx.doi.org/10.1109/83.605414[Crossref]
  • [11] S. Didas, B. Burgeth, A. Imiya, J. Weickert, Scale Space and PDE Methods in Computer Vision 3459, 13 (2005) http://dx.doi.org/10.1007/11408031_2[Crossref]
  • [12] B. Ninness, IEEE T. Inf. Theory 44, 32 (1998) http://dx.doi.org/10.1109/18.650986[Crossref]
  • [13] I. Petras, D. Sierociuk, I. Podlubny, IEEE T. Signal Proces. 60, 5561 (2012) http://dx.doi.org/10.1109/TSP.2012.2205920[Crossref]
  • [14] Y. F. Pu, J. L. Zhou, X. Yuan, IEEE T. Image Process. 19, 491 (2010) http://dx.doi.org/10.1109/TIP.2009.2035980[Crossref]
  • [15] B. Jian, X. C. Feng, IEEE T. Image Process. 16, 2492 (2007) http://dx.doi.org/10.1109/TIP.2007.904971[Crossref]
  • [16] P. Guidotti, J. V. Lambers, J. Math. Imaging Vis. 33, 25 (2009) http://dx.doi.org/10.1007/s10851-008-0108-z[Crossref]
  • [17] E. Cuesta, M. Kirane, S. A. Malik, Signal Process. 92, 553 (2012) http://dx.doi.org/10.1016/j.sigpro.2011.09.001[Crossref]
  • [18] M. Janev, S. Pilipovic, T. Atanackovic, R. Obradovic, N. Ralevic, Math. Comput. Model. 54, 729 (2011) http://dx.doi.org/10.1016/j.mcm.2011.03.017[Crossref]
  • [19] D. Chen, H. Sheng, Y. Q. Chen, D. Y. Xue, Phil. Trans. R. Soc. A., DOI:10.1098/rsta.2012.0148 [Crossref]
  • [20] D. Hunter, K. Lange, The American Statistician 58, 30 (2004) http://dx.doi.org/10.1198/0003130042836[Crossref]
  • [21] M. A. T. Figueiredo, J. M. Bioucas-Dias, R. D. Nowak, IEEE T. Image Process. 16, 2980 (2007) http://dx.doi.org/10.1109/TIP.2007.909318[Crossref]
  • [22] J. P. Oliveira, J. M. Bioucas-Dias, M. A. T. Figueiredo, Signal Process. 89, 1683 (2009) http://dx.doi.org/10.1016/j.sigpro.2009.03.018[Crossref]
  • [23] I. Podlubny, Fractional Calculus and Applied Analysis 3, 359 (2000)
  • [24] I. Podlubny, Fractional Differential Equations (Academic Press, San Diego, 1999)
  • [25] P. Perona, J. Malik, IEEE T. Pattern Anal. 12, 629 (1990) http://dx.doi.org/10.1109/34.56205[Crossref]
  • [26] S. G. Armato, et al., Med. Phys. 38, 915 (2011) http://dx.doi.org/10.1118/1.3528204[Crossref]
  • [27] R. C. Gonzalez, R. E. Woods, Digital Image Processing, 2nd edition (Addison-Wesley, Massachusetts, 1992)
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_2478_s11534-013-0241-1
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.