Improvements on "Fast space-variant elliptical filtering using box splines"

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Kunal Narayan Chaudhury, Sebanti Sanyal

Abstract

It is well-known that box filters can be efficiently computed using pre-integration and local finite-differences. By generalizing this idea and by combining it with a nonstandard variant of the central limit theorem, we had earlier proposed a constant-time or O(1) algorithm that allowed one to perform space-variant filtering using Gaussian-like kernels. The algorithm was based on the observation that both isotropic and anisotropic Gaussians could be approximated using certain bivariate splines called box splines. The attractive feature of the algorithm was that it allowed one to continuously control the shape and size (covariance) of the filter, and that it had a fixed computational cost per pixel, irrespective of the size of the filter. The algorithm, however, offered a limited control on the covariance and accuracy of the Gaussian approximation. In this paper, we propose some improvements of our previous algorithm.

References

Sep 1, 2009·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Arrate Muñoz-BarrutiaCarlos Ortiz-de-Solorzano
Mar 31, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Kunal Narayan ChaudhuryMichael Unser

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