Coherence Enhancing Diffusion and Windowed Fourier Filtering for Fringe Patterns Denoising (II)

Abstract

Fringe patterns produced by various optical interferometric techniques encode the information of deformation, refractive index, vibration, etc. Noise as one of the key problems affects further processing of the fringe patterns and reduces the final measurement quality. Coherence enhancing diffusion (CED) is a partial differential equation based denoising model that suppresses the noise as well as preserves the flow‐like structure. Windowed Fourier transform‐based windowed Fourier filtering (WFF) is another useful fringe pattern denoising tool that removes noise by thresholding the windowed Fourier transform spectrum. An adaptive windowed Fourier filtering (AWFF) that denoises the fringe pattern based on pixels’ local frequencies is proposed in this paper. The performance of AWFF is compared with WFF and CED by applying them to fringe patterns that contain speckle noise and different levels of frequencies. Quantitative results will be given on simulated fringe patterns. Experimental fringe pattern will also be tested to illustrate the performance of these methods.