Shy, Douglas and Perona, Pietro (1994) X-Y separable pyramid steerable scalable kernels. In: Proceedings, 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition: June 21-23, 1994, Seattle, Washington. IEEE , Los Alamitos, CA, pp. 237-244. http://resolver.caltech.edu/CaltechAUTHORS:SHYcvpr94
See Usage Policy.
Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:SHYcvpr94
A new method for generating X-Y separable, steerable, scalable approximations of filter kernels is proposed which is based on a generalization of the singular value decomposition (SVD) to three dimensions. This “pseudo-SVD” improves upon a previous scheme due to Perona (1992) in that it reduces convolution time and storage requirements. An adaptation of the pseudo-SVD is proposed to generate steerable and scalable kernels which are suitable for use with a Laplacian pyramid. The properties of this method are illustrated experimentally in generating steerable and scalable approximations to an early vision edge-detection kernel.
|Item Type:||Book Section|
|Additional Information:||© Copyright 1994 IEEE. The authors wish to acknowledge the following people: Mike Burl for his suggestions and work regarding the pyramid scheme; Thomas Leung for debugging the matlab code and helping with implementation; Jan de Leeuw and Steve Breiner for pointing out previous work done on 3D tensor decomposition.|
|Subject Keywords:||steerable; scalable filters; multi-resolution; SVD; pyramid; multi-orientation filtering; early vision; multi-way arrays|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Tony Diaz|
|Deposited On:||07 Jun 2006|
|Last Modified:||26 Dec 2012 08:54|
Repository Staff Only: item control page