Change search
ReferencesLink to record
Permanent link

Direct link
Color Persistent Anisotropic Diffusion of Images
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6096-3648
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-7557-4904
2011 (English)In: Image Analysis / [ed] Anders Heyden, Fredrik Kahl, Heidelberg: Springer, 2011, 262-272 p.Conference paper (Refereed)
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.

Place, publisher, year, edition, pages
Heidelberg: Springer, 2011. 262-272 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 6688
Keyword [en]
Non-linear diffusion, color image processing, perceptual image quality
National Category
Information Science Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:liu:diva-68999DOI: 10.1007/978-3-642-21227-7_25ISBN: 978-3-642-21226-0 (print)ISBN: 978-3-642-21227-7 (print)OAI: diva2:424137
The 17th Scandinavian Conference on Image Analysis, 23-27 May 2011, Ystad Sweden

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. Copyright: Springer

Available from: 2011-06-17 Created: 2011-06-15 Last updated: 2016-08-31Bibliographically approved
In thesis
1. A Variational Approach to Image Diffusion in Non-Linear Domains
Open this publication in new window or tab >>A Variational Approach to Image Diffusion in Non-Linear Domains
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
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

Place, publisher, year, edition, pages
Linköping University Electronic Press, 2013. 32 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1594
National Category
Signal Processing
urn:nbn:se:liu:diva-92788 (URN)LIU-TEK-LIC-2013:28 (Local ID)978-91-7519-606-0 (ISBN)LIU-TEK-LIC-2013:28 (Archive number)LIU-TEK-LIC-2013:28 (OAI)
2013-06-13, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Available from: 2013-05-30 Created: 2013-05-22 Last updated: 2016-05-04Bibliographically approved

Open Access in DiVA

fulltext(10252 kB)701 downloads
File information
File name FULLTEXT01.pdfFile size 10252 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Freddie, ÅströmMichael, FelsbergReiner, Lenz
By organisation
Computer VisionThe Institute of TechnologyMedia and Information Technology
Information ScienceComputer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 701 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 569 hits
ReferencesLink to record
Permanent link

Direct link