Document Detail


Maximum SNR pattern strategy for phase shifting methods in structured light illumination.
MedLine Citation:
PMID:  20808403     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
Structured light illumination by means of phase shifting patterns is a widely employed method for three-dimensional (3-D) image acquisition that is robust to ambient light and object albedo but may be especially susceptible to sensor and environment noise. In this paper, we study the specific technique of phase measuring profilometry (PMP) and the maximization of a pattern's signal to noise ratio (SNR). By treating the design of an N-pattern PMP process as placing points in an N-dimensional coding space, we define a pattern's SNR in terms of a pattern set's computational length and the number of coded phase periods in the projected patterns. Then, without introducing phase ambiguities, we propose a so-called edge pattern strategy that maximizes the computational length and number of periods. Theoretically, the edge pattern technique improves the SNR by 1.2381 times when using three component patterns and by 15.5421 times when using five patterns. Experimental results further demonstrate the improved SNR of the proposed edge pattern technique such that more accurate 3-D results are achieved using fewer component patterns.
Authors:
Yongchang Wang; Kai Liu; Daniel L Lau; Qi Hao; Laurence G Hassebrook
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of the Optical Society of America. A, Optics, image science, and vision     Volume:  27     ISSN:  1520-8532     ISO Abbreviation:  J Opt Soc Am A Opt Image Sci Vis     Publication Date:  2010 Sep 
Date Detail:
Created Date:  2010-09-02     Completed Date:  2011-01-19     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9800943     Medline TA:  J Opt Soc Am A Opt Image Sci Vis     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1962-71     Citation Subset:  -    
Affiliation:
Center for Visualization and Virtual Environments, University of Kentucky, Lexington, Kentucky 40507, USA.
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