Adaptive phase denoising based on first order local polynomial analysis

This paper concentrates on the optical interferometry wrapped phase denoising method. A new adaptive denoising algorithm based on the local polynomial approximation is researched. Firstly, the local polynomial analysis is studied and the polynomial parameters are estimated by the proposed method which combines the Windowed Fast Fourier Transform with the gradient ascent method. Then the adaptive data window sizes are determined by the proposed largest window size with acceptable hypothesis method. One improvement is that our algorithm uses the first order polynomial method to select adaptive window sizes and to do the phase approximation. At last, a set of experiments are shown to prove that the proposed method can compromise between preventing noise and preserving original phase details.