Speckle noise reduction in quantitative optical metrology techniques by application of the discrete wavelet transformation

Cosme Furlong; Ryszard J. Pryputniewicz

doi:10.1117/12.472228

20 June 2002 Speckle noise reduction in quantitative optical metrology techniques by application of the discrete wavelet transformation

Cosme Furlong, Ryszard J. Pryputniewicz

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Proceedings Volume 4777, Interferometry XI: Techniques and Analysis; (2002) https://doi.org/10.1117/12.472228
Event: International Symposium on Optical Science and Technology, 2002, Seattle, WA, United States

Abstract

Effective suppression of speckle noise content in interferometric data images can help in improving accuracy and resolution of the results obtained with interferometric optical metrology techniques. In this paper, novel speckle noise reduction algorithms based on the discrete wavelet transformation are presented. The algorithms proceed by: (a) estimating the noise level contained in the interferograms of interest, (b) selecting wavelet families, (c) applying the wavelet transformation using the selected families, (d) wavelet thresholding, and (e) applying the inverse wavelet transformation, producing denoised interferograms. The algorithms are applied to the different stages of the processing procedures utilized for generation of quantitative speckle correlation interferometry data of fiber-optic based opto-electronic holography (FOBOEH) techniques, allowing identification of optimal processing conditions. It is shown that wavelet algorithms are effective for speckle noise reduction while preserving image features otherwise faded with other algorithms.

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Cosme Furlong and Ryszard J. Pryputniewicz "Speckle noise reduction in quantitative optical metrology techniques by application of the discrete wavelet transformation", Proc. SPIE 4777, Interferometry XI: Techniques and Analysis, (20 June 2002); https://doi.org/10.1117/12.472228

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KEYWORDS

Speckle

Wavelets

Denoising

Interferometry

Discrete wavelet transforms

CCD cameras

Image processing

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