Noise reduction in digital speckle pattern interferometry using bidimensional empirical mode decomposition

Abstract

We propose a bidimensional empirical mode decomposition (BEMD) method to reduce speckle noise in digital speckle pattern interferometry (DSPI) fringes. The BEMD method is based on a sifting process that decomposes the DSPI fringes in a finite set of subimages represented by high and low frequency oscillations, which are named modes. The sifting process assigns the high frequency information to the first modes, so that it is possible to discriminate speckle noise from fringe information, which is contained in the remaining modes. The proposed method is a fully data-driven technique, therefore neither fixed basis functions nor operator intervention are required. The performance of the BEMD method to denoise DSPI fringes is analyzed using computer-simulated data, and the results are also compared with those obtained by means of a previously developed one-dimensional empirical mode decomposition approach. An application of the proposed BEMD method to denoise experimental fringes is also presented.