文章基本信息

标题：Depth from Defocus Based on Geometric Constraints
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作者：Wu, Qiufeng ; Wang, Kuanquan ; Zuo, Wangmeng 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2014
卷号：9
期号：1
页码：44-51
DOI：10.4304/jcp.9.1.44-51
语种：English
出版社：Academy Publisher
摘要：This paper proposes a Depth from Defocus (DFD) model based on geometric constraints. The two measured defocused images match with each other with this method including geometric constraints, which bypasses estimation of the radiance. These geometric constraints vary with different relative position of image plane and image focus. The experimental results on the synthetic and real images show that this method is accurate and efficient. The experimental results on the synthetic images with noise show that this method is robust to the images with Salt &Pepper and Poisson noise.
关键词：depth from defocus;relative spread of point spread function;geometric constraints