Threshold selection in transform-domain denoising of speckle pattern fringes

Abstract

A transform-domain fringe pattern denoising technique is presented. The Discrete Cosine Transform (DCT) is applied in a sliding window manner to get an overcomplete image expansion, and then the transform coefficients are thresholded to reduce the noise. We investigate the proper size of the sliding window and the proper threshold level. The latter is determined individually for each window position using a local noise variance estimate. In order to deal with a rather inadequate but simplified noise model, a proportionality factor, related with the speckle size, is found by experiments with digitally simulated speckle fringes. Such a proportionality factor suggests that the technique could be made fully automatic. We demonstrate promising results in denoising of real speckle fringe patterns, obtained through an out-of-plane sensitive Digital Speckle Pattern Interferometry (DSPI) set-up in a process of non-destructive testing of reinforced composite materials deformation.