华南理工大学学报(自然科学版) ›› 2010, Vol. 38 ›› Issue (4): 136-140.doi: 10.3969/j.issn.1000-565X.2010.04.025

• 计算机科学与技术 • 上一篇    下一篇

基于相对模糊和边缘强化的散焦求深度方法

章权兵 张爱明   

  1. 安徽大学 计算智能与信号处理教育部重点实验室, 安徽 合肥 230039
  • 收稿日期:2009-04-07 修回日期:2009-10-16 出版日期:2010-04-25 发布日期:2010-04-25
  • 通信作者: 章权兵(1977-),男,博士,副教授,主要从事计算机视觉与图像处理研究. E-mail:qbzhang@ahu.edu.cn
  • 作者简介:章权兵(1977-),男,博士,副教授,主要从事计算机视觉与图像处理研究.
  • 基金资助:

    国家自然科学基金资助项目(60603083 60872106)

Depth Recovery from Defocus Based on Relative Blur and Edge Enhancement

Zhang Quan-bing  Zhang Ai-ming   

  1. Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education,Anhui University,Hefei 230039,Anhui,China
  • Received:2009-04-07 Revised:2009-10-16 Online:2010-04-25 Published:2010-04-25
  • Contact: 章权兵(1977-),男,博士,副教授,主要从事计算机视觉与图像处理研究. E-mail:qbzhang@ahu.edu.cn
  • About author:章权兵(1977-),男,博士,副教授,主要从事计算机视觉与图像处理研究.
  • Supported by:

    国家自然科学基金资助项目(60603083 60872106)

摘要: 通过改进Favaro等人提出的迭代求解热扩散方程的方法,研究了由散焦图像恢复物体深度的问题.首先将两幅散焦图像按照不同的相对模糊程度划分为两个区域,证明了这两个区域的边界和图像的边缘有很高的一致性;然后通过强化图像的边缘,使这两个区域的边界在迭代求解热扩散方程的过程中更容易确定;再根据确定的U+和U-的边界较好地求解了物体深度;最后通过模拟实验及实际图像实验对该方法进行了验证.模拟实验结果表明,文中方法具有较好的鲁棒性;实际算例分析表明,文中方法的恢复效果优于Favaro的方法

关键词: 散焦求深度, 热扩散, 相对模糊, 图像边缘

Abstract:

This paper deals with the depth recovery from defocused images by improving Favaro's iteration method based on thermal diffusion equations.In the investigation,two defocused images are respectively divided into two regions according to the relative blur,whose borders are highly consistent with the image edge and can be easily determined by strengthening the image edge during the solving of the thermal diffusion equation via iteration.The depth can be accurately obtained according to the determined U+ and U-boundaries.The effectiveness of the proposed method is then validated by simulation and real image experiment.Simulated results show that the proposed method is of high robustness,and the real-image experimental results show that the method is superior to Favaro's method in terms of depth recovery.

Key words: defocused image, depth recovery, thermal diffusion, relative blur, image edge