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An advanced electronic phase stepped interferometry (EPSI) system is described for quantitative out-of-plane displacement and surface topography measurements for NDE applications. Image processing algorithms were developed using novel techniques to extend the sensitivity of EPSI and provide near real-time measurement capability. EPSI is known to provide out-ofplane displacement and surface topography measurements on the order of 1/20-1/100 microns. Noise can be a limiting factor, however, and robust phase unwrapping, which is required, remains an open and active research area. A prototype ESPI system was developed and tested using simulated and real data sets of known displacement fields. A robust maximumlikelihood binary-tree (MLBT) phase unwrapping technique was developed, providing greater robustness in the presence of noise than standard techniques. In addition, the MLBT algorithm lends itself to efficient and fast parallel implementations for near-real time implementation. A rank conditioned median (RCM) filter was also tested for improved system performance through noise suppression. The use of these advanced algorithms improves the capabilities of existing EPSI techniques, providing more robustness and near real-time measurements. Results are provided for deformations in Ti-6Al-4V and Al2024-T3 aerospace materials.

Phase-stepped interferometry is a well known technique for the measurement of surface deformation. Since in this technique phase characteristics of a linear system is computed using the arctangent function, in some points the raw phase data exceeds the value 2. Moreover the surface roughness, phase unwrapping, and extra noise imposed from the environment makes the surface look like an original surface with huge impulsive noise and simply using PSI technique does not produce an accurately reconstructed surface. In this paper, a filtering technique is proposed that suppresses the noise and enhances the image quality. It is shown that the raw phase data prefiltered by a mean filter eliminates Gaussian noise. Then, after proper unwrapping treatment, the data should be filtered with a rank conditioned median (RCM) filter. The RCM filter is very effective at treating impulsive type noise while preserving step edges without blurring. © 1999 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(99)01911-X]

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