Evaluation of Mean, Gaussian and S&G aggregation windows in stereo correspondence under presence of noise

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

Abstract

Few topics in image processing have been as extensively studied as stereo correspondence, these algorithms can be divided into two categories, local and global, depending on how the processing is done in the image. A stereo correspondence algorithm is called local if operate on sections of the images and global this treatment is performed on the entire images. In local algorithms specifically, this aggregation window is used for smoothing volume pairing cost, so that a better match is performed in presence of fronto-parallel regions. This article presents a comparison between Mean, Gaussian and Savitzky-Golay aggregation windows in local algorithms, analyzing the noise in test images and how the selection of the aggregation window affects the performance of the stereo matching algorithm.

Original languageEnglish
Title of host publicationSymposium of Signals, Images and Artificial Vision - 2013, STSIVA 2013
DOIs
StatePublished - 2013
Event2013 18th Symposium of Image, Signal Processing, and Artificial Vision, STSIVA 2013 - Bogota, Colombia
Duration: 11 Sep 201313 Sep 2013

Publication series

NameSymposium of Signals, Images and Artificial Vision - 2013, STSIVA 2013

Conference

Conference2013 18th Symposium of Image, Signal Processing, and Artificial Vision, STSIVA 2013
Country/TerritoryColombia
CityBogota
Period11/09/1313/09/13

Keywords

  • Mean Shift
  • Savitzky-Golay
  • Stereo
  • digital differentiators
  • image segmentation
  • smoothing filter

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