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Proceedings Paper

Robust depth-from-defocus for autofocusing in the presence of image shifts
Author(s): Younsik Kang; Xue Tu; Satyaki Dutta; Murali Subbarao
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Paper Abstract

A new passive ranging technique named Robust Depth-from-Defocus (RDFD) is presented for autofocusing in digital cameras. It is adapted to work in the presence of image shift and scale change caused by camera/hand/object motion. RDFD is similar to spatial-domain Depth-from-Defocus (DFD) techniques in terms of computational efficiency, but it does not require pixel correspondence between two images captured with different defocus levels. It requires approximate correspondence between image regions in different image frames as in the case of Depth-from-Focus (DFF) techniques. Theory and computational algorithm are presented for two different variations of RDFD. Experimental results are presented to show that RDFD is robust against image shifts and useful in practical applications. RDFD also provides insight into the close relation between DFF and DFD techniques.

Paper Details

Date Published: 29 August 2008
PDF: 10 pages
Proc. SPIE 7066, Two- and Three-Dimensional Methods for Inspection and Metrology VI, 706609 (29 August 2008); doi: 10.1117/12.792769
Show Author Affiliations
Younsik Kang, SUNY at Stony Brook (United States)
Xue Tu, SUNY at Stony Brook (United States)
Satyaki Dutta, SUNY at Stony Brook (United States)
Murali Subbarao, SUNY at Stony Brook (United States)


Published in SPIE Proceedings Vol. 7066:
Two- and Three-Dimensional Methods for Inspection and Metrology VI
Peisen S. Huang; Toru Yoshizawa; Kevin G. Harding, Editor(s)

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