Denoising and extracting background from fringe patterns using midpoint-based bidimensional empirical mode decomposition

Maciej Wielgus; Krzysztof Patorski

doi:10.1117/12.2047586

17 December 2013 Denoising and extracting background from fringe patterns using midpoint-based bidimensional empirical mode decomposition

Maciej Wielgus, Krzysztof Patorski

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Proceedings Volume 9066, Eleventh International Conference on Correlation Optics; 90660K (2013) https://doi.org/10.1117/12.2047586
Event: Eleventh International Conference on Correlation Optics, 2013, Chernivsti, Ukraine

Abstract

We propose a 2D generalization to the midpoint-based empirical mode decomposition algorithm (MBEMD). Unlike with the regular bidimensional empirical mode decomposition algorithm (BEMD), we do not interpolate the upper and lower envelopes, but rather directly find the mean envelope, utilizing well defined points between two extrema of different kind (midpoints). This approach has several advantages such as improved spectral selectivity and better time performance over the regular BEMD process. The MBEMD algorithm is then applied to the task of the interferometric fringe pattern analysis, to identify its distinct components. This allows to separate the oscillatory pattern component, which is of interest, from the background, noise and possibly other spurious interferometric patterns. In result, the phase demodulation error is reduced. Flexibility of the adaptive method allows for processing correlation fringe patterns met in the digital speckle pattern interferometry as well as the regular interferometric fringe patterns without any special tuning of the algorithm.

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Maciej Wielgus and Krzysztof Patorski "Denoising and extracting background from fringe patterns using midpoint-based bidimensional empirical mode decomposition", Proc. SPIE 9066, Eleventh International Conference on Correlation Optics, 90660K (17 December 2013); https://doi.org/10.1117/12.2047586

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KEYWORDS

Fringe analysis

Interferometry

Denoising

Image processing

Speckle pattern

Demodulation

Filtering (signal processing)

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