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

摘要

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 kinds (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 separating the oscillatory pattern component, which is of interest, from the background, noise, and possibly other spurious interferometric patterns. Such an enhancement is meant to aid further phase demodulation and reduce its errors. 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.