Vector-valued image interpolation by an anisotropic diffusion-projection PDE

Roussos, A; Maragos, P

dc.contributor.author	Roussos, A	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:45:00Z
dc.date.available	2014-03-01T02:45:00Z
dc.date.issued	2007	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32086
dc.subject	Anisotropic Diffusion	en
dc.subject	Color Image	en
dc.subject	Image Interpolation	en
dc.subject	Interpolation Method	en
dc.subject	Nonlinear Diffusion	en
dc.subject.other	Anisotropy	en
dc.subject.other	Computational geometry	en
dc.subject.other	Interpolation	en
dc.subject.other	Mathematical models	en
dc.subject.other	Nonlinear analysis	en
dc.subject.other	Appropriate smoothing	en
dc.subject.other	Blurring	en
dc.subject.other	Diffusion flow	en
dc.subject.other	Vector-valued images	en
dc.subject.other	Image analysis	en
dc.title	Vector-valued image interpolation by an anisotropic diffusion-projection PDE	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-72823-8_10	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-72823-8_10	en
heal.publicationDate	2007	en
heal.abstract	We propose a nonlinear image interpolation method, based on an anisotropic diffusion PDE and designed for the general case of vector-valued images, The interpolation solution is restricted to the subspace of functions that can recover the discrete input image, after an appropriate smoothing and sampling, The proposed nonlinear diffusion flow lies on this subspace and its strength and anisotropy effectively adapt to the local variations and geometry of image structures, The derived model efficiently reconstructs the real image structures, leading to a natural interpolation, with reduced blurring, staircase and ringing artifacts of classic methods. This method also outperforms other existing PDE-based interpolation methods. We present experimental results that prove the potential and efficacy of the method as applied to graylevel and color images. © Springer-Verlag Berlin Heidelberg 2007.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-72823-8_10	en
dc.identifier.volume	4485 LNCS	en
dc.identifier.spage	104	en
dc.identifier.epage	115	en