Fast fringe enhancement by improved bidimensional sinusoids-assisted empirical mode decomposition

Abstract

Fringe enhancement is necessary for optical measurement, which includes the elimination of noise and background from a fringe pattern. Bidimensional empirical mode decomposition (BEMD) algorithms have been used for fringe enhancement, but they usually decompose a fringe pattern into many bidimensional intrinsic mode functions (BIMFs), which is not only inefficient but also leads to difficulties for classifying the BIMFs to distinguish noise, the useful signal and background. In this paper, the bidimensional sinusoids-assisted empirical mode decomposition (BSEMD) algorithm is firstly studied in depth, and a key factor is found in deciding the results. Then an improved BSEMD (iBSEMD) algorithm is proposed, where the key factor is estimated easily and automatically. The proposed method largely reduces the number of BIMFs resulted, making the fringe enhancement become faster and have a more robust effect. Some optimized strategies are given additionally to implement the iBSEMD algorithm by compute unified device architecture (CUDA) for practical applications. Comparison experiments are conducted with state-of-the-art methods to prove the efficiency and effectiveness of our method.