计算机科学 ›› 2026, Vol. 53 ›› Issue (6A): 250800043-5.doi: 10.11896/jsjkx.250800043

• 图像处理&多媒体技术 • 上一篇    下一篇

基于改进加权引导滤波的立体匹配算法

张奔1, 朱灯林2   

  1. 1 南京交通职业技术学院轨道交通学院 南京 211188
    2 河海大学机电工程学院 江苏 常州 213022
  • 出版日期:2026-06-16 发布日期:2026-06-12
  • 通讯作者: 张奔(runebenny@gmail.com)
  • 基金资助:
    江苏省高等学校自然科学研究项目(18KJD510008)

Improved Stereo Matching Algorithm Based on Weighted Guided Image Filtering

ZHANG Ben1, ZHU Denglin2   

  1. 1 College of Rail Transport,Nanjing Vocational Institute of Transport Technology,Nanjing 211188,China
    2 College of Mechanical and Electrical Engineering,Hohai University,Changzhou,Jiangsu 213022,China
  • Published:2026-06-16 Online:2026-06-12
  • About author:ZHANG Ben,born in 1984,Ph.D,assistant professor.His main research in-terests include robotics,image proces-sing and machine vision.
  • Supported by:
    Natural Science Foundation of the Jiangsu Higher Education Institutions of China(18KJD510008).

摘要: 为了实现实时有效的立体匹配,在现有的局部立体匹配算法的基础上,提出了一种基于加权引导滤波的局部立体匹配算法。首先,在代价计算阶段采用多测度融合的方法。其次,在成本聚集阶段,采用加权引导滤波方法进行滤波,利用Canny算法自适应调整正则化参数,实现了更精确的成本聚集。最后,对WTA优化策略得到的视差图进行左右一致性检测(LRC)的致密化处理。通过对Middlebury数据库的图像采用该算法进行立体匹配,结果验证了算法的有效性和鲁棒性。

关键词: 立体匹配, 局部匹配, 引导滤波, 加权因子

Abstract: In order to achieve real-time and effective stereo matching,this paper proposes a local stereo matching algorithm based on weighted guided filtering based on the existing local stereo matching algorithms.Firstly,the matching costs are computation based on multi-measures.Then in the cost aggregation stage,the weighted guided filtering method is used to guide the filtering,the regularization parameters are adjusted adaptively to achieve more accurate cost aggregation by Canny method.Finally,disparity maps obtained by WTA optimization strategy are processed by densification after LRC.The proposed algorithm is applied to stereo matching of images in Middlebury database,and the experimental results verify that the proposed algorithm is effective and robustness.

Key words: Stereo matching, Local matching, Guided filtering, Weighting factor

中图分类号: 

  • TN911.73
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