计算机应用 ›› 2014, Vol. 34 ›› Issue (3): 824-827.DOI: 10.11772/j.issn.1001-9081.2014.03.0824

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于差值绝对值之和和置信传播的快速收敛立体匹配算法

张丽红,何树成   

  1. 山西大学 物理电子工程学院,太原030006
  • 收稿日期:2013-09-24 修回日期:2013-11-20 出版日期:2014-03-01 发布日期:2014-04-01
  • 通讯作者: 张丽红
  • 作者简介:张丽红(1968-),女,河北赵县人,副教授,主要研究方向:图像处理、模式识别;何树成(1987-),男,山西晋城人,硕士研究生,主要研究方向:图像处理、机器视觉。
  • 基金资助:

    山西省高校高新技术产业化项目

Fast convergent stereo matching algorithm based on sum of absolute difference and belief propagation

ZHANG Lihong,HE Shucheng   

  1. College of Physics and Electronic Engineering, Shanxi University, Taiyuan Shanxi 030006, China
  • Received:2013-09-24 Revised:2013-11-20 Online:2014-03-01 Published:2014-04-01
  • Contact: ZHANG Lihong

摘要:

针对传统置信传播(BP)立体匹配算法运算次数较多、效率低下的问题,提出了一种基于像素灰度绝对误差和(SAD)和BP的快速收敛立体匹配算法。首先使用SAD作为代价函数来计算初始视差值,并将可靠视差值作为约束项加入全局算法BP的能量函数中,进行全局的能量函数的优化;然后在优化过程中更新计算每个像素点的置信度时,考虑当前像素点自适应大小邻域内像素点对它的信息传递,而忽略距离较远的像素点的影响,从而减少了置信传播节点数并提高了置信度收敛的速度。实验结果表明,提出的算法在保持相近匹配精度的前提下,运行时间减少了50%~60%,提高了立体匹配效率,为实时应用打下了基础。

关键词: 立体匹配, 初始视差, 能量函数, 置信传播, 快速收敛

Abstract:

Concerning the high computation complexity and low efficiency in traditional stereo matching method based on Belief Propagation (BP), a fast convergent stereo matching algorithm based on Sum of Absolute Difference (SAD) algorithm and BP algorithm was proposed. Firstly, the SAD matching method was used as a similarity decision criterion to determine the initial disparity map. When the energy function was constructed, the initial parallax map was used as a limit of function to get the optimization of disparity distribution by BP. And when calculating the confidence level of each pixel in the optimization process, the algorithm only utilized the information translated from the neighboring pixels in an adaptive support window, while ignoring the impact of the pixels beyond the window, then the nodes of BP were reduced and the convergence speed was improved. The experimental results show that the proposed algorithm can reduce matching computation time by 50%-60% and improve efficiency while maintaining the matching accuracy, and the proposed algorithm lays the foundation for the real-time applications.

Key words: stereo matching, initial disparity, energy function, belief propagation(BP), fast convergence

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