Unsupervised-clustering-driven noise-residue filter for phase images

We analyze the characteristics of noise-induced phase inconsistencies, or residues, in a wrapped phase map. Because residues are the potential source of phase-error propagation, it is essential to filter them before two-dimensional phase unwrapping. We propose an unsupervised-clustering-driven noise-residue filter, and apply it as a preprocessing procedure of phase unwrapping. The filter is based on the fact that most residues are present in the form of adjacency caused by noisy wrapped phases. These noisy phases differ from the other correct ones numerically within the local k(1) x k(2) window containing the adjacent residues, and it is possible to group the correct and noisy wrapped phases into different clusters. The window size is determined adaptively according to the local noise level. The proposed procedure avoids constructing branch cuts, and converts path-following unwrapping to path independence, which improves the operating speed of phase unwrapping significantly. The tests performed on simulated and real projected fringe patterns confirm the validity of our approach in residue reduction, fringe preservation, and rapidity.