Cosine integral images for fast spatial and range filtering

Elhanan Elboher, Michael Werman

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

Abstract

Non uniform kernels is important for many image processing algorithms. However, for large kernel sizes the filtering can become computationally expensive. We introduce cosine integral images (CII) which represent a large set of spatial and range filters, based on their frequency decomposition. The filtering requires a constant number of operations per image pixel, independent of filter size. We make use of CII to compute the Gabor filters, whose complexity is for the first time a constant O(1) operations per image pixel. We also improve previous constant time approximations of spatial Gaussian smoothing and bilateral filtering.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages89-92
Number of pages4
DOIs
StatePublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 11 Sep 201114 Sep 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/TerritoryBelgium
CityBrussels
Period11/09/1114/09/11

Keywords

  • Gabor filter
  • Gaussian filter
  • Non uniform filtering
  • bilateral filter
  • cosine transform
  • integral images

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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