Fast algorithm for local stereo matching in disparity estimation

Yu Cheng Tseng*, Tian-Sheuan Chang

*Corresponding author for this work

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

2 Scopus citations

Abstract

The typical local stereo matching for disparity estimation can deliver accurate disparity maps by a well-designed cost aggregation method, but usually suffers from natively high computational complexity due to its dense processing. To address it, we propose a fast algorithm with search point reduction on spatial and disparity domains to generate a sparse search map. The sparse search map guides the local stereo matching to produce a sparse disparity map, and then it is recovered to a dense disparity map. The experimental results show the proposed fast algorithm could reduce the computation time to 8.8% of original algorithm for 2-megapixel images, and only has slightly quality degradation by 0.92dB in final view synthesis images.

Original languageEnglish
Title of host publication17th DSP 2011 International Conference on Digital Signal Processing, Proceedings
DOIs
StatePublished - 29 Sep 2011
Event17th International Conference on Digital Signal Processing, DSP 2011 - Corfu, Greece
Duration: 6 Jul 20118 Jul 2011

Publication series

Name17th DSP 2011 International Conference on Digital Signal Processing, Proceedings

Conference

Conference17th International Conference on Digital Signal Processing, DSP 2011
CountryGreece
CityCorfu
Period6/07/118/07/11

Keywords

  • Disparity estimation
  • Fast algorithm
  • Stereo matching

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