Noisy Phase Unwrap for Fringe Techniques: Adaptive Local Polynomial Approximations

Many imaging systems deal with phase measurements using coherent radiation in order to illuminate objects. The reflected scattered return carries information on physical and geometrical properties of illuminated objects. It can be information on shape, deformation, movement and structure of the object's surface. We propose a novel phase unwrap filtering for noisy holographic data. Based on the window size adaptive local polynomial approximation it allows dramatically reduce level of noise and in the same time preserve phase variation features. Simulation shows that the technique enables an advanced accuracy for phase reconstruction from wrapped noisy observations.