Volume 9 Number 1 (Jan. 2014)
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JCP 2014 Vol.9(1): 44-51 ISSN: 1796-203X
doi: 10.4304/jcp.9.1.44-51

Depth from Defocus Based on Geometric Constraints

Qiufeng Wu1, 2, Kuanquan Wang1, Wangmeng Zuo1
1School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
2College of Science, Northeast Agricultural University, Harbin, China


Abstract—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.

Index Terms—depth from defocus, relative spread of point spread function, geometric constraints

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Cite: Qiufeng Wu, Kuanquan Wang, Wangmeng Zuo, "Depth from Defocus Based on Geometric Constraints," Journal of Computers vol. 9, no. 1, pp. 44-51, 2014.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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