Non-Gaussian Scale Space Filtering with 2 by 2 Matrix of Linear Filters
Computer Vision and Pattern Recognition
2011-10-06 v1
Abstract
Construction of a scale space with a convolution filter has been studied extensively in the past. It has been proven that the only convolution kernel that satisfies the scale space requirements is a Gaussian type. In this paper, we consider a matrix of convolution filters introduced in [1] as a building kernel for a scale space, and shows that we can construct a non-Gaussian scale space with a matrix of filters. The paper derives sufficient conditions for the matrix of filters for being a scale space kernel, and present some numerical demonstrations.
Keywords
Cite
@article{arxiv.1110.0872,
title = {Non-Gaussian Scale Space Filtering with 2 by 2 Matrix of Linear Filters},
author = {Toshiro Kubota},
journal= {arXiv preprint arXiv:1110.0872},
year = {2011}
}