Full-text resources of PSJD and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


Preferences help
enabled [disable] Abstract
Number of results

Journal

2013 | 11 | 10 | 1414-1422

Article title

Fractional-order TV-L2 model for image denoising

Content

Title variants

Languages of publication

EN

Abstracts

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.

Publisher

Journal

Year

Volume

11

Issue

10

Pages

1414-1422

Physical description

Dates

published
1 - 10 - 2013
online
19 - 12 - 2013

Contributors

author
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
author
  • 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
author
  • MESA Lab, University of California, Merced, 5200 North Lake Road, Merced, CA, 95343, USA
author
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China

References

  • [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)

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.-psjd-doi-10_2478_s11534-013-0241-1
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.