Fast Space-Variant Elliptical Filtering Using Box Splines Articles uri icon

publication date

  • September 2010

start page

  • 2290

end page

  • 2306


  • 9


  • 19

International Standard Serial Number (ISSN)

  • 1057-7149


  • The efficient realization of linear space-variant (non-convolution) filters is a challenging computational problem in image processing. In this paper, we demonstrate that it is possible to filter an image with a Gaussian-like elliptic window of varying size, elongation and orientation using a fixed number of computations per pixel. The associated algorithm, which is based upon a family of smooth compactly supported piecewise polynomials, the radially-uniform box splines, is realized using preintegration and local finite-differences. The radially-uniform box splines are constructed through the repeated convolution of a fixed number of box distributions, which have been suitably scaled and distributed radially in an uniform fashion. The attractive features of these box splines are their asymptotic behavior, their simple covariance structure, and their quasi-separability. They converge to Gaussians with the increase of their order, and are used to approximate anisotropic Gaussians of varying covariance simply by controlling the scales of the constituent box distributions. Based upon the second feature, we develop a technique for continuously controlling the size, elongation and orientation of these Gaussian-like functions. Finally, the quasi-separable structure, along with a certain scaling property of box distributions, is used to efficiently realize the associated space-variant elliptical filtering, which requires O (1) computations per pixel irrespective of the shape and size of the filter.


  • iltering; gaussian processes; gaussian approximation; gaussian distribution; nonlinear filters; image processing; pixel; polynomials; finite difference methods; convolution; author keywords; anisotropic gaussian; box spline; finite differences; running sums; space variant filter; zwart-powell (zp) element; box splines; finite difference; gaussians; anisotropy; asymptotic analysis; pixels; splines; algorithm; article; diagnostic imaging; fluorescence microscopy; human; methodology; normal distribution; algorithms; humans; image processing; computer assisted