Efficient and accurate Gaussian image filtering using running sums

Elhanan Elboher*, Michael Werman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

This paper presents a simple and efficient method to convolve an image with a Gaussian kernel. The computation is performed in a constant number of operations per pixel using running sums along the image rows and columns. We investigate the error function used for kernel approximation and its relation to the properties of the input signal. Based on natural image statistics we propose a quadratic form kernel error function so that the SSD error of the output image is minimized. We apply the proposed approach to approximate the Gaussian kernel by linear combination of constant functions. This results in a very efficient Gaussian filtering method. Our experiments show that the proposed technique is faster than state of the art methods while preserving similar accuracy.

Original languageAmerican English
Title of host publicationProceedings of the 2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012
Pages897-902
Number of pages6
DOIs
StatePublished - 2012
Event2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012 - Kochi, India
Duration: 27 Nov 201229 Nov 2012

Publication series

NameInternational Conference on Intelligent Systems Design and Applications, ISDA
ISSN (Print)2164-7143
ISSN (Electronic)2164-7151

Conference

Conference2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012
Country/TerritoryIndia
CityKochi
Period27/11/1229/11/12

Keywords

  • Gaussian kernel
  • Non uniform filtering
  • integral images
  • natural image statistics

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