Library Subscription: Guest
Begell Digital Portal Begell Digital Library eBooks Journals References & Proceedings Research Collections
Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Print: 0040-2508
ISSN Online: 1943-6009

Volume 78, 2019 Volume 77, 2018 Volume 76, 2017 Volume 75, 2016 Volume 74, 2015 Volume 73, 2014 Volume 72, 2013 Volume 71, 2012 Volume 70, 2011 Volume 69, 2010 Volume 68, 2009 Volume 67, 2008 Volume 66, 2007 Volume 65, 2006 Volume 64, 2005 Volume 63, 2005 Volume 62, 2004 Volume 61, 2004 Volume 60, 2003 Volume 59, 2003 Volume 58, 2002 Volume 57, 2002 Volume 56, 2001 Volume 55, 2001 Volume 54, 2000 Volume 53, 1999 Volume 52, 1998 Volume 51, 1997

Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v59.i12.150
8 pages

Application of Fractal Compression Methods for Image Filtering

I. V. Barishev
National Aerospace University (Kharkov Aviation Institute), 17, Chkalov St., Kharkov, 61070, Ukraine
M. L. Uss
National Aerospace University (Kharkov Aviation Institute), 17, Chkalov St., Kharkov, 61070


Filtering is one of the principal tasks of image processing. This problem is especially complicated due to the fact that images are very inhomogeneous in their structure and can be corrupted by additive, multiplicative or pulse interferences [1,2]. The algorithm of filtering has to solve two contradictory challenges - to suppress noise and to save boundaries and minor details in the picture. By now plenty of algorithms for filtering [1,2] have been developed, although improvement of the quality of saving boundaries and minor details still remains a crucial task for the present time.
Image filtering presumes a choice of a certain image model. A properly chosen model allows to describe the image with the prescribed accuracy, but providing for less amount of information. On the basis of the above model it is possible to carry out both compression and filtering of images, at that, the quality of both compression and filtering are usually rigidly bound. Presently, fractal compression methods [3], using self-similarity of the image at various scaling, are among the best compression algorithms, still very little attention is paid to the development of the methods of filtering based on this idea in special literature [4]. Therefore, an attempt to apply the ideas of fractal compression for image filtering has been undertaken in this paper.