A New Image Demising Method Based on Partial Differential Equations

Article Preview

Abstract:

In the paper, we discuss the image demising models, based on partial differential equations. It is through the use of the concept of variations in the calculus of the objective function minimization problem, defines the image processing tasks. The results show that the model expands 2d thermal diffusion equation. Therefore, it is easy to get solution is to use a simple iterative process.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

22-26

Citation:

Online since:

October 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Garage dean P. R., Partial Differential Equations, John Wiley and Sons, New York 1(6), 114-118 (1964).

Google Scholar

[2] Kenwood Kang Chris Weinberger, Wei Caiman Short Essay on Variation Calculus", Stanford University 2(6), 112-115 (2010).

Google Scholar

[3] Huber's Robust Statistics, Wiley, New York 3(5), 211-214 (1981).

Google Scholar

[4] Rodin. L, Ocher. S, Fatima. E Nonlinear total variation based noise removal algorithms, Physical 4(8), 259-268 (2010).

Google Scholar

[5] Carter. J Dual Methods for Total Variation-based Image Restoration, PhD thesis, UCLA, Los Angeles, CA 5(9), 181-184 (2001).

Google Scholar

[6] Chamblee. A"An algorithm for total variation minimizations and applications", Journal Math. Imaging Vis 6(11), 191-195 (2011).

Google Scholar

[7] Chamblee. A, Total variation minimization and a class of binary MRF models in Energy Minimization Methods, Computer Vision and Pattern Recognition 7(4), 136-152 (2011).

DOI: 10.1007/11585978_10

Google Scholar