欢迎访问中国科学院大学学报,今天是

中国科学院大学学报 ›› 2011, Vol. 28 ›› Issue (5): 630-635.DOI: 10.7523/j.issn.2095-6134.2011.5.010

• 论文 • 上一篇    下一篇

一种采用自适应机制的分层置信传播算法

池凌鸿, 郭立, 郁理, 陈运必   

  1. 中国科学技术大学电子科学与技术系, 合肥 230027
  • 收稿日期:2010-07-20 修回日期:2010-11-15 发布日期:2011-09-15
  • 基金资助:

    国家自然科学基金(61071173)资助 

A self-adaptive hierarchical belief propagation algorithm

CHI Ling-Hong, GUO Li, YU Li, CHEN Yun-Bi   

  1. Department of Electronic Science and Technology, USTC, Hefei 230027, China
  • Received:2010-07-20 Revised:2010-11-15 Published:2011-09-15

摘要:

提出了一种基于迭代自适应机制的改进算法,有效地缩减了分层置信传播算法(HBP)的计算时间.传统HBP计算时间随指定的迭代上限增加而线性增长.为此引入消息收敛的条件判断,在迭代上限相同情况下,减少算法的迭代次数,缩减整体迭代时间.实验表明,与传统HBP相比,该方法计算时间缩减了38%以上,计算时间对整体迭代上限不敏感.该方法可以应用于使用HBP算法的其他方法.

关键词: 置信传播, 自适应, 立体匹配, 图像修复

Abstract:

We propose a self-adaptive algorithm with convergence detection to reduce the computational complexity of HBP. In the conventional HBP, the computational complexity linearly increases with specified iteration upper bound. We introduce convergence detection to stop the iteration of messages which have already converged to optimal values. Experimental results show that the self-adaptive algorithm reduces computational time by 38% or more, and the computational time is insensitive to iteration upper bound. The convergence detection methodology can be used in other HBP-related applications.

Key words: belief propagation, self-adaptive, stereo match, restoration

中图分类号: