Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Van der Weken, Dietrich; 1 | Nachtegael, Mike; 2 | Kerre, Etienne E.; 3
Affiliations: Fuzziness and Uncertainty Modelling Research Unit, Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 (Building S9), 9000 Gent, Belgium
Note: [1] E-mail: dietrich.vanderweken@rug.ac.be.
Note: [2] E-mail: mike.nachtegael@rug.ac.be.
Note: [3] E-mail: etienne.kerre@rug.ac.be.
Abstract: Objective quality measures or measures of comparison are of great importance in the field of image processing. These measures serve as a tool to evaluate and to compare different algorithms designed to solve problems, such as noise reduction, deblurring, compression … Consequently these measures serve as a basis on which one algorithm is preferred to another. It is well-known that classical quality measures, such as the MSE (mean square error) or the PSNR (peak signal to noise ratio), not always correspond to visual observations. Therefore, several researchers are—and have been—looking for new quality measures, better adapted to human perception. The existing similarity measures are all pixel-based, and have therefore not always satisfactory results. To cope with this drawback, we propose a similarity measure based on a neighborhood, so that the relevant structures of the images are observed very well. The new similarity measure is designed especially for the use in image processing.
Keywords: Image processing, similarity measures, image similarity, fuzzy sets
Keywords: 95D05, 68U10
DOI: 10.3233/JCM-2003-3202
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 3, no. 2, pp. 209-222, 2003
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl