Fringe patterns are widely used in the optical interferometry. The captured fringe patterns usually have noises, and thus a filtering process for fringe patterns is necessary. The windowed Fourier filtering (WFF) algorithm is proposed specially for fringe pattern denoising. The WFF performs well in continuous areas, but has problems in discontinuous areas. In this paper, we proposed a hybrid denoising scheme which combines the advantages of the local WFF algorithm and non-local block-matching 3D filtering (BM3D) algorithm. This new scheme can recover fringe pattern information from the WFF residuals, and improve the denoising results effectively.
Optical interferometry is a popular technique for high precision measurement. It produces fringe patterns for analysis. The output fringe patterns usually have noises, and thus a filtering process for fringe patterns is necessary. A few filtering algorithms, such as windowed Fourier filtering (WFF), have been proposed specially for fringe pattern denoising. Meanwhile, filtering techniques have been intensively studied for a long time in the general image processing area. It is curious that how the filtering techniques in general image processing area perform on fringe pattern denoising. In this paper, a state-of-the-art filtering algorithm, block-matching 3D filtering (BM3D), is selected and compared with the WFF.
Windowed Fourier ridges algorithm can provide a quality map to assist the quality-guided phase unwrapping. Its performance for discontinuous phase maps is investigated in this paper, where the influence of window size in the algorithm is examined. Three discontinuous phase boundaries, straight, curved, and fused, are tested for both noiseless and noisy situations. Encouraging results are observed. Small window size can be used for higher boundary detection accuracy and can be enlarged if noise is heavy and/or the discontinuities are not obvious in a small area.