Depth from Defocus Technique Based on Cross Reblurring

Kazumi TAKEMURA  Toshiyuki YOSHIDA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.11   pp.2083-2092
Publication Date: 2019/11/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2019PCP0004
Type of Manuscript: Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
Category: 
Keyword: 
depth from defocus (DFD),  depth estimation,  multi-focus images,  blur,  telecentric optics,  pixel disalignment,  

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Summary: 
This paper proposes a novel Depth From Defocus (DFD) technique based on the property that two images having different focus settings coincide if they are reblurred with the opposite focus setting, which is referred to as the “cross reblurring” property in this paper. Based on the property, the proposed technique estimates the block-wise depth profile for a target object by minimizing the mean squared error between the cross-reblurred images. Unlike existing DFD techniques, the proposed technique is free of lens parameters and independent of point spread function models. A compensation technique for a possible pixel disalignment between images is also proposed to improve the depth estimation accuracy. The experimental results and comparisons with the other DFD techniques show the advantages of our technique.