DATA-DEPENDENT SYSTEMS METHODOLOGY FOR NOISE-INSENSITIVE PHASE UNWRAPPING IN LASER INTERFEROMETRIC SURFACE CHARACTERIZATION

Phase unwrapping recovers the actual surface topography from a calcula ted phase map, which is often degraded by a combination of surface def ects and measurement noise. Prevalent unwrapping techniques are unable to differentiate between the surface and noise-created discontinuitie s, resulting in an improper surface recovery. In our approach the stoc hastic nature of the phase map is used by the data-dependent systems ( DDS) methodology to separate the surface from noisy measurements. The DDS methodology identifies an adequate autoregressive moving-average m odel representing the measured phase values. An adaptive thresholding scheme carries out the phase discontinuity removal from the model resi duals, employing statistical outlier detection. We then recover the su rface by using the model and clean residuals. The proposed technique i s found useful for unwrapping especially noisy and degraded phase maps .