CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

Reaction-Diffusion System with Additional Source Term Applied to Image Restoration

by Jimin Yu, Jiayong Ye, Shangbo Zhou
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 2
Year of Publication: 2016
Authors: Jimin Yu, Jiayong Ye, Shangbo Zhou
10.5120/ijca2016910998

Jimin Yu, Jiayong Ye, Shangbo Zhou . Reaction-Diffusion System with Additional Source Term Applied to Image Restoration. International Journal of Computer Applications. 147, 2 ( Aug 2016), 18-23. DOI=10.5120/ijca2016910998

@article{ 10.5120/ijca2016910998,
author = { Jimin Yu, Jiayong Ye, Shangbo Zhou },
title = { Reaction-Diffusion System with Additional Source Term Applied to Image Restoration },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 2 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number2/25625-2016910998/ },
doi = { 10.5120/ijca2016910998 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:50:49.233544+05:30
%A Jimin Yu
%A Jiayong Ye
%A Shangbo Zhou
%T Reaction-Diffusion System with Additional Source Term Applied to Image Restoration
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 2
%P 18-23
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many noisy texture images require the enhancement of coherent structures in various applications. Traditional TV-based methods make the denoising fail when the data-fitting weight parameter λ is strong, on the contrary, reducing the corresponding parameter λ may distort the textures, and generate staircase artifacts. Therefore in order to smooth the image efficiently, the suitable λ shall be adopted. Formally minimizing the TV-based energy functional yields the associated Euler-Lagrange equation, which can be seen as a reaction-diffusion system, in general the corresponding parameter λ with respect to reaction term is always small to ensure sufficiently removal of the noise,and this feature has the contrast between coherent structures and the background decreased. Hence in this paper a reaction-diffusion system is investigated applied to image restoration with additional source term embedded into the system. Subsequently, this new model combines contrast enhancement with diffusion processes, so it may be more suitable for dealing with Gaussian white noise than the original models. The proposed method is assessed in terms of the theoretical and numerical properties changed by the source term. Finally, An experimental result is also given to demonstrate the efficiency of this kind of model.

References
  1. L.Rudin, S.Osher, E.Fatemi, Nonlinear total variation based noise removal algorithms, Physica D 60, pp. 259-268(1992).
  2. R.Acar, C.R.Vogel, Analysis of bounded variation penalty methods for ill-posed problems, Inverse Probl.10, pp. 1217-1229(1994).
  3. P.Blomgren, T.F.Chan, P.Mulet, C.Wong, Total variation image restoration: numerical methods and extensions, in: Proceedings of the 1997 IEEE International Conference on Image Processing, pp. 1217-1229 (1997).
  4. V.Caselles, J.-M.Morel, C.Sbert, An axiomatic approach to image interpolation, IEEE Trans. Image Process.7, pp. 376-386(1998).
  5. A.Chambolle, P.L.Lions, Image recovery via total variation minimization and related problems, Numer. Math.76, pp. 167-188(1997).
  6. S.Osher, A.Sole, L.Vese, Image decomposition and restoration using total variation minimization and the H^(-1) norm, SIAM: Multiscale Model Sim.1, pp. 349-370(2003).
  7. Y.Meyer, Oscillating Patterns in Image Processing and Nonlinear Evolution Equations, in: Univ. Lecture Ser., AMS, (2002).
  8. M.Lashgari, H.Rabbani, M.Shahmorad, M.Swain, A fast and accurate dental micro-CT image denoising based on total variation modeling, 2015 IEEE Workshop on Signal Processing Systems, (2015).
  9. Ming-Te Chi, Wei-Ching Liu, Shu-Hsuan Hsu, Image stylization using anisotropic reaction diffusion, The Visual Computer, vol.31, pp. 1-13(2015).
  10. Vicent Caselles, Jean-Michel Morel, Guillermo Sapiro, Allen Tannenbaum, Introduction to the special issue on partial differential equations and geometry-driven diffusion in image processing and analysis, Georgia Institute of Technology, pp. 269-273 (1998).
  11. C.M.Elliott, S.A.McBeth, Analysis of the TV regularization and H^(-1) fidelity model for decomposing an image into cartoon plus texture, Commun. Pur. Appl. Anal.6(4), pp. 917-936(2007).
  12. Z.Guo, J.Yin, Q.Liu, On a reaction-diffusion system applied to image decomposition and restoration, Mathematicaland Computer Modelling, vol. 53, no. 5-6, pp. 1336-1350(2011).
  13. Joachim Weickert, Coherence-enhancing shock filters, Pattern Recognition, Springer, pp. 1-8(2003).
  14. László Szirmay, Milán Magdics, Balázs Tóth, Volume enhancement with externally controlled anisotropic diffusion, The Visual Computer, vol. 32, pp. 1-12(2016).
  15. Boguslaw Obara, Mark Fricker, Vicente Grau, Coherence enhancing diffusion filtering based on the phase congruency tensor, in: 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 202-205(2012).
  16. G.Dong, Z.Guo, Z.Zhou, D.Zhang, B.Wo,Coherence-enhancing diffusion with the source term, Applied Mathematical Modelling. 39, pp. 6060-6072(2015).
  17. M Neri, ERRS Zara, Simultaneous Image Inpainting and Denoising with TV-Based Active Set Method, Taiwan-philippines Symposium on Analysis, (2015).
  18. P.Perona and J.Malik, Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, no.7, pp. 629-639(1990).
  19. Black M.J., G.Sapiro, D.Marimont, D.Heeger, Robust anisotropic diffusion, vol. 7,No 3,(1998).
  20. J.Weickert, Anisotropic diffusion in image processing. B.g.teubner Stuttgart, Germany(1998).
  21. Gilles Aubert, Pierre Kornprobst, Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations, vol. 147, Springer, (2006).
Index Terms

Computer Science
Information Sciences

Keywords

Image restoration Reaction-diffusion system Source term Texture enhancement