DocumentCode :
2797782
Title :
Efficient Laplacian feature map pyramids in a hexagonal framework
Author :
Coleman, Sonya ; Scotney, Bryan ; Gardiner, Bryan
Author_Institution :
Sch. of Comput. & Intell. Syst., Univ. of Ulster, Londonderry, UK
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
1466
Lastpage :
1469
Abstract :
A systematic design procedure is used to develop Laplacian operators that facilitate the computation of hexagonal feature map pyramids. Our focus is the development of algorithms that can operate on hexagonal images over a range of scales. We show how scalable operators can be explicitly constructed using a Gaussian neighbourhood function. We extend this approach to achieve an efficient approximation via a feature map pyramid that implicitly embodies operator scaling. In both cases we provide performance evaluation with respect to edge localisation.
Keywords :
Gaussian processes; Laplace equations; edge detection; feature extraction; Gaussian neighbourhood function; Laplacian feature map pyramid; edge localisation; hexagonal framework; hexagonal image; operator scaling; Feature extraction; Filter bank; Finite element methods; Focusing; Image processing; Image reconstruction; Image representation; Intelligent systems; Laplace equations; Pixel; Feature map pyramid; Hexagonal operators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495487
Filename :
5495487
Link To Document :
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