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dc.contributor.authorBerryman, Fiona
dc.contributor.authorPynsent, Paul
dc.contributor.authorCubillo, James
dc.date.accessioned2008-04-16T10:55:41Z
dc.date.available2008-04-16T10:55:41Z
dc.date.issued2004
dc.identifier.citationOptics and Lasers in Engineering, 41(6): 815-825
dc.identifier.doi10.1016/S0143-8166(03)00061-7
dc.identifier.urihttp://hdl.handle.net/2436/23572
dc.description.abstractThis paper analyses the effectiveness of windowing to reduce errors in Fourier transform profilometry (FTP). Various levels of random noise have been added to simulated digital images of a spherical dome illuminated by fringes projected from an offset angle. The noisy images have been analysed using FTP with various window functions applied to the data before the forward Fourier transform. The theoretical dome was subtracted from the reconstructed domes to give error maps. The maximum and root mean square errors were calculated and plotted against the added noise level. At very low levels of added noise applying a pre-transform window produced considerably lower errors, nearly 50% lower for the Blackman window with no added noise. However, above around 10% added noise the reductions in the errors were reduced to only a few per cent. Whether pre-transform windowing is worthwhile therefore depends strongly on the noise content of the images.
dc.language.isoen
dc.publisherElsevier Science Direct
dc.relation.urlhttp://www.sciencedirect.com/science/journal/01438166
dc.subjectFourier Transform Profilometry
dc.subjectWindowing
dc.subjectRandom noise
dc.titleThe effect of windowing in Fourier transform profilometry applied to noisy images
dc.typeJournal article
dc.identifier.journalOptics and Lasers in Engineering
html.description.abstractThis paper analyses the effectiveness of windowing to reduce errors in Fourier transform profilometry (FTP). Various levels of random noise have been added to simulated digital images of a spherical dome illuminated by fringes projected from an offset angle. The noisy images have been analysed using FTP with various window functions applied to the data before the forward Fourier transform. The theoretical dome was subtracted from the reconstructed domes to give error maps. The maximum and root mean square errors were calculated and plotted against the added noise level. At very low levels of added noise applying a pre-transform window produced considerably lower errors, nearly 50% lower for the Blackman window with no added noise. However, above around 10% added noise the reductions in the errors were reduced to only a few per cent. Whether pre-transform windowing is worthwhile therefore depends strongly on the noise content of the images.


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