Design of fast multidimensional filters using genetic algorithms
2005 (English)In: Applications of Evolutionary Computing: EvoWorkkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC Lausanne, Switzerland, March 30 - April 1, 2005 Proceedings, Springer Berlin/Heidelberg, 2005, 366-375 p.Conference paper (Refereed)
A method for designing fast multidimensional filters using genetic algorithms is described. The filter is decomposed into component filters where coefficients can be sparsely scattered using filter networks. Placement of coefficients in the filters is done by genetic algorithms and the resulting filters are optimized using an alternating least squares approach. The method is tested on a 2-D quadrature filter and the method yields a higher quality filter in terms of weighted distortion compared to other efficient implementations that require the same ammount of computations to apply. The resulting filter also yields lower weighted distortion than the full implementation.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005. 366-375 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3449
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-28771DOI: 10.1007/978-3-540-32003-6_37Local ID: 13951ISBN: 978-3-540-25396-9 (print)ISBN: 978-3-540-32003-6 (online)OAI: oai:DiVA.org:liu-28771DiVA: diva2:249583
7th European Workshop on Evolutionary Computing in Image Analysis and Signal Processing,2005, Lausanne, Switzerland, 30 March - 1 April 2005