We describe a phase-shifting out-of-plane speckle interferometer operating at 1 kHz for studying dynamic events. The system is based on a Pockels cell that is synchronized to a high-speed video camera to ensure that the phase shifting occurs between frames. Phase extraction is performed by use of a standard four-frame algorithm, and temporal phase unwrapping allows sequences of several hundred absolute (rather than relative) displacement maps to be obtained fully automatically. The maximum theoretical surface velocity of 67 microm s(-1) is a factor of 40 greater than can be achieved with a speckle interferometer based on a conventional video camera. We test the system using a target that is displaced with constant speed in a direction normal to its surface by means of a piezoelectric transducer. The system's performance in a practical situation is illustrated with measurements on a thin plate undergoing out-of-plane deformation.
Current whole-field interferometric techniques yield a phase distribution in modulo 2π. Removal of the resulting cyclic discontinuities is a process known as unwrapping, which must be performed before the data can be interpreted. We investigate an iterative unwrapping technique recently published by Ghiglia and Romero [J. Opt. Soc. Am. A 11, 107 (1994)], which is based on least-squares minimization, obtained by the discrete cosine transform. We apply this technique to remove phase wraps from electronic speckle pattern interferometry data, using modest personal computer hardware. The algorithm is shown to be fast, easy to implement, robust in the presence of noise, and able to handle phase inconsistencies without propagating local errors.
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.
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