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Color Persistent Anisotropic Diffusion of Images
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0002-6096-3648
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0001-7557-4904
2011 (engelsk)Inngår i: Image Analysis / [ed] Anders Heyden, Fredrik Kahl, Heidelberg: Springer, 2011, s. 262-272Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Techniques from the theory of partial differential equations are often used to design filter methods that are locally adapted to the image structure. These techniques are usually used in the investigation of gray-value images. The extension to color images is non-trivial, where the choice of an appropriate color space is crucial. The RGB color space is often used although it is known that the space of human color perception is best described in terms of non-euclidean geometry, which is fundamentally different from the structure of the RGB space. Instead of the standard RGB space, we use a simple color transformation based on the theory of finite groups. It is shown that this transformation reduces the color artifacts originating from the diffusion processes on RGB images. The developed algorithm is evaluated on a set of real-world images, and it is shown that our approach exhibits fewer color artifacts compared to state-of-the-art techniques. Also, our approach preserves details in the image for a larger number of iterations.

sted, utgiver, år, opplag, sider
Heidelberg: Springer, 2011. s. 262-272
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 6688
Emneord [en]
Non-linear diffusion, color image processing, perceptual image quality
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-68999DOI: 10.1007/978-3-642-21227-7_25ISBN: 978-3-642-21226-0 (tryckt)ISBN: 978-3-642-21227-7 (tryckt)OAI: oai:DiVA.org:liu-68999DiVA, id: diva2:424137
Konferanse
The 17th Scandinavian Conference on Image Analysis, 23-27 May 2011, Ystad Sweden
Merknad

Original Publication: Åström Freddie, Felsberg Michael and Lenz Reiner, Color Persistent Anisotropic Diffusion of Images, 2011, Image Analysis, SCIA conference, 23-27 May 2011, Ystad Sweden, 262-272. http://dx.doi.org/10.1007/978-3-642-21227-7_25 Copyright: Springer

Tilgjengelig fra: 2011-06-17 Laget: 2011-06-15 Sist oppdatert: 2018-02-06bibliografisk kontrollert
Inngår i avhandling
1. A Variational Approach to Image Diffusion in Non-Linear Domains
Åpne denne publikasjonen i ny fane eller vindu >>A Variational Approach to Image Diffusion in Non-Linear Domains
2013 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Image filtering methods are designed to enhance noisy images captured in situations that are problematic for the camera sensor. Such noisy images originate from unfavourable illumination conditions, camera motion, or the desire to use only a low dose of ionising radiation in medical imaging. Therefore, in this thesis work I have investigated the theory of partial differential equations (PDE) to design filtering methods that attempt to remove noise from images. This is achieved by modeling and deriving energy functionals which in turn are minimized to attain a state of minimum energy. This state is obtained by solving the so called Euler-Lagrange equation. An important theoretical contribution of this work is that conditions are put forward determining when a PDE has a corresponding energy functional. This is in particular described in the case of the structure tensor, a commonly used tensor in computer vision.A primary component of this thesis work is to model adaptive image filtering such that any modification of the image is structure preserving, but yet is noise suppressing. In color image filtering this is a particular challenge since artifacts may be introduced at color discontinuities. For this purpose a non-Euclidian color opponent transformation has been analysed and used to separate the standard RGB color space into uncorrelated components.A common approach to achieve adaptive image filtering is to select an edge stopping function from a set of functions that have proven to work well in the past. The purpose of the edge stopping function is to inhibit smoothing of image features that are desired to be retained, such as lines, edges or other application dependent characteristics. Thus, a step from ad-hoc filtering based on experience towards an application-driven filtering is taken, such that only desired image features are processed. This improves what is characterised as visually relevant features, a topic which this thesis covers, in particular for medical imaging.The notion of what are relevant features is a subjective measure may be different from a layman's opinion compared to a professional's. Therefore, we advocate that any image filtering method should yield an improvement not only in numerical measures but also a visual improvement should be experienced by the respective end-user

sted, utgiver, år, opplag, sider
Linköping University Electronic Press, 2013. s. 32
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1594
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-92788 (URN)LIU-TEK-LIC-2013:28 (Lokal ID)978-91-7519-606-0 (ISBN)LIU-TEK-LIC-2013:28 (Arkivnummer)LIU-TEK-LIC-2013:28 (OAI)
Presentation
2013-06-13, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (engelsk)
Opponent
Veileder
Prosjekter
NACIP, VIDI, GARNICS
Tilgjengelig fra: 2013-05-30 Laget: 2013-05-22 Sist oppdatert: 2016-05-04bibliografisk kontrollert

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