Local stereo matching with improved matching cost and disparity refinement

Jianbo Jiao*, Ronggang Wang, Wenmin Wang, Shengfu Dong, Zhenyu Wang, Wen Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

63 Citations (Scopus)


Recent local stereo matching methods have achieved comparable performance with global methods. However, the final disparity map still contains significant outliers. In this article, the authors propose a local stereo matching method that employs a new combined cost approach and a secondary disparity refinement mechanism. They formulate combined cost using a modified color census transform and truncated absolute differences of color and gradients. They also use symmetric guided filter for cost aggregation. Unlike in traditional stereo matching, they propose a novel secondary disparity refinement to further remove the remaining outliers. Experimental results on the Middlebury benchmark show that their method ranks fifth out of 153 submitted methods, and it's the best cost-volume filtering-based local method. Experiments on real-world sequences and depth-based applications also validate the proposed method's effectiveness.

Original languageEnglish
Pages (from-to)16-27
Number of pages12
JournalIEEE Multimedia
Issue number4
Early online date9 Sept 2014
Publication statusPublished - Oct 2014

Bibliographical note

Publisher Copyright:
© 2014 IEEE.


  • Benchmark testing
  • Disparity refinement
  • Image color analysis
  • Image edge detection
  • Matching cost
  • Multimedia
  • Radar
  • Research and development
  • Stereo matching
  • Stereo vision
  • Transforms

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Media Technology
  • Hardware and Architecture
  • Computer Science Applications


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