Phase Local Approximation (PhaseLa) Technique for Phase Unwrap From Noisy Data

The local polynomial approximation (LPA) is a nonparametric regression technique with pointwise estimation in a sliding window. We apply the LPA of the argument of cos and sin in order to estimate the absolute phase from noisy wrapped phase data. Using the intersection of confidence interval (ICI) algorithm the window size is selected as adaptive pointwise varying. This adaptation gives the phase estimate with the accuracy close to optimal in the mean squared sense. For calculations we use a Gauss-Newton recursive procedure initiated by the phase estimates obtained for the neighboring points. It enables tracking properties of the algorithm and its ability to go beyond the principal interval [-, ) and to reconstruct the absolute phase from wrapped phase observations even when the magnitude of the phase difference takes quite large values. The algorithm demonstrates a very good accuracy of the phase reconstruction which on many occasion overcomes the accuracy of the state-of-the-art algo...

• Type: Journal
• Year: 2008
• Where: TIP
• Authors: Vladimir Katkovnik, Jaakko Astola, Karen O. Egiazarian
• Keywords: Absolute Phase, Algorithm, Noisy Wrapped Phase, TIP 2008