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Robust Focus Measure Operator Using Adaptive Log-Polar Mapping for Three-Dimensional Shape Recovery

Published online by Cambridge University Press:  10 March 2015

Ik-Hyun Lee
Affiliation:
Media Lab, Massachusetts Institute of Technology, Cambridge, MA, 02139USA
Muhammad Tariq Mahmood
Affiliation:
School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeolno, Byeogchunmyun, Cheonan, Chungnam 330-708, Republic of Korea
Tae-Sun Choi*
Affiliation:
School of Mechatronics, Gwangju Institute of Science and Technology, 123 Cheomdan Gwagiro, Buk-Gu, Gwangju 500-712, Republic of Korea
*
*Corresponding author. tschoi@gist.ac.kr
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Abstract

Shape from focus (SFF) is a passive optical technique that reconstructs object shape from a sequence of image taken at different focus levels. In SFF techniques, computing focus measurement for each pixel in the image sequence, through a focus measure operator, is the fundamental step. Commonly used focus measure operators compute focus quality in Cartesian space and suffer from erroneous focus quality and lack in robustness. Thus, they provide erroneous depth maps. In this paper, we introduce a new focus measure operator that computes focus quality in log-polar transform (LPT) Properties of LPT, such as biological inspiration, data selection, and edge invariance, enable computation of better focus quality in the presence of noise. Moreover, instead of using a fixed patch of the image, we suggest the use of an adaptive window. The focus quality is assessed by computing variation in LPT. The effectiveness of the proposed technique is evaluated by conducting experiments using image sequences of different simulated and real objects. The comparative analysis shows that the proposed method is robust and effective in the presence of various types of noise.

Type
Materials Applications
Copyright
© Microscopy Society of America 2015 

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