Abstract
Non-local functionals have been successfully applied in a variety of applications, such as spectroscopy or in general filtering of time-dependent data. We mention the patch-based denoising of image sequences [Boulanger et al. IEEE Transactions on Medical Imaging (2010)]. Another family of non-local functionals considered in these notes approximates total variation denoising. Thereby we rely on fundamental characteristics of Sobolev spaces and the space of functions of finite total variation (see [Bourgain et al. Journal d’Analyse Mathématique 87, 77–101 (2002)] and several follow up papers). Standard results of the calculus of variations, like for instance the relation between lower semi-continuity of the functional and convexity of the integrand, do not apply, in general, for the non-local functionals. In this paper we address the questions of the calculus of variations for non-local functionals and derive relations between lower semi-continuity of the functionals and separate convexity of the integrand. Moreover, we use the new characteristics of Sobolev spaces to derive novel approximations of the total variation energy regularisation. All the functionals are well-posed and reveal a unique minimising point. Even more, existing numerical schemes can be recovered in this general framework.
AMS 2010 Subject Classification: 49J05, 49J45, 49M25
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aubert, G., Kornprobst, P.: Can the nonlocal characterization of Sobolev spaces by Bourgain et al. be useful for solving variational problems? SIAM Journal on Numerical Analysis 47, 844 (2009)
Bevan, J., Pedregal, P.: A necessary and sufficient condition for the weak lower semicontinuity of one-dimensional non-local variational integrals. Proc. Roy. Soc. Edinburgh Sect. A 136, 701–708 (2006)
Boulanger, J., Kervrann, C., Salamero, J., Sibarita, J.-B., Elbau, P., Bouthemy, P.: Patch-based non-local functional for denoising fluorescence microscopy image sequences. IEEE Transactions on Medical Imaging (2010)
Bourgain, J., Brézis, H., Mironescu, P.: Another look at Sobolev spaces. In: Optimal Control and Partial Differential Equations, IOS Press, Amsterdam (2001)
Bourgain, J., Brézis, H., Mironescu, P.: Limiting embedding theorems for W s, p when s↑ 1 and applications. Journal d’Analyse Mathématique 87, 77–101 (2002)
Buades, A., Coll, B., Morel, J.-M.: A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation 4, 490–530 (2006)
Buades, A., Coll, B., Morel, J.-M.: Neighborhood filters and PDEs. Numerische Mathematik 105, 1–34 (2006)
Efros, A.A., Leung, T.K.: Texture synthesis by non-parametric sampling. International Conference on Computer Vision 2, 1033–1038 (1999)
Elbau, P.: Sequential lower semi-continuity of non-local functionals. Arxiv preprint (2011)
Fonseca, I., Leoni, G.: Modern methods in the calculus of variations: Lp spaces. Springer (2007)
Gilboa, G., Osher, S.: Nonlocal operators with applications to image processing. Multiscale Modeling and Simulation 7, 1005–1028 (2008)
Kindermann, S., Osher, S., Jones, P.W.: Deblurring and denoising of images by nonlocal functionals. Multiscale Modeling and Simulation 4, 1091–1115 (2006)
Mahmoudi, M., Sapiro, G.: Fast image and video denoising via nonlocal means of similar neighborhoods. IEEE Signal Processing Letters 12, 839 (2005)
Muñoz, J.: On some necessary conditions of optimality for a nonlocal variational principle. SIAM J. Control Optim. 38, 1521–1533 (2000)
Muñoz, J.: Extended variational analysis for a class of nonlocal minimization principles. Nonlinear Anal. 47, 1413–1418 (2001)
Muñoz, J.: Characterisation of the weak lower semicontinuity for a type of nonlocal integral functional: the n-dimensional scalar case. J. Math. Anal. Appl. 360, 495–502 (2009)
Pedregal, P.: Nonlocal variational principles. Nonlinear Analysis 29, 1379–1392 (1997)
Ponce, A.C.: A new approach to Sobolev spaces and connections to Γ-convergence. Calculus of Variations and Partial Differential Equations 19, 229–255 (2004)
Pontow, C., Scherzer, O.: A derivative-free approach to total variation regularization. Arxiv preprint arXiv:0911.1293 (2009)
Smith, S.M., Brady, J.M.: SUSAN – A new approach to low level image processing. International Journal of Computer Vision 23, 45–78 (1997)
Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of the Sixth International Conference on Computer Vision, Volume 846 (1998)
Vogel, C.R.: Computational methods for inverse problems. Frontiers in Mathematics, Volume 23. SIAM (2002)
Yaroslavsky, L.P., Yaroslavskij, L.P.: Digital picture processing: An introduction. Springer (1985)
Acknowledgements
The work of CP and OS has been supported by the Austrian Science Fund (FWF) within the research networks NFNs Industrial Geometry, Project S09203, and Photoacoustic Imaging in Biology and Medicine, Project S10505-N20.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Boulanger, J., Elbau, P., Pontow, C., Scherzer, O. (2011). Non-Local Functionals for Imaging. In: Bauschke, H., Burachik, R., Combettes, P., Elser, V., Luke, D., Wolkowicz, H. (eds) Fixed-Point Algorithms for Inverse Problems in Science and Engineering. Springer Optimization and Its Applications(), vol 49. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9569-8_8
Download citation
DOI: https://doi.org/10.1007/978-1-4419-9569-8_8
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-9568-1
Online ISBN: 978-1-4419-9569-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)