A novel method of eliminating the background in Fourier transform profilometry based on Bi-dimensional Empirical Mode Decomposition

Abstract

To address the issue of spectrum overlapping in Fourier transform profilometry, a new method based on Bi-dimensional Empirical Mode Decomposition (BEMD) is proposed. BEMD is an adaptive data decomposition method, so it does not need filters or basic functions which are important for Fourier transform or wavelet transform. In this paper, the complicated original signal of distorted fringe pattern is decomposed into several Bi-dimensional Intrinsic Mode Functions (BIMFs) as well as the residual component, with which the background component and some other frequency noises of fringe pattern can be eliminated effectively. It is beneficial to extract the first frequency component exactly for the subsequent wrapped phase retrieval in Fourier transform. Simulation and experiments illustrate the feasibility and the exactness of the proposed method.