Denoising phase unwrapping algorithm for precise phase shifting interferometry

Abstract

Phase unwrapping refers to the process of recovering the absolute phase ϕ from a wrapped phase φ. Phase unwrapping arise in many applications, such as wavefront measurements in interferometry, field mapping in magnetic resonance imaging, the interferometry SAR process, measurements in adaptive optics and even a deflectometry. Gaining attention for a long time, many algorithms have been developed in relation to phase unwrapping problem. Jose’s phase unwrapping algorithm via graph cuts (PUMA) is one of the most efficient algorithms given its ability to process various phase types with high accuracy levels. However, the drawback of PUMA is its computation speed when processing large complex phases, and its lack of a pre-filter, which raises issues when processing noisy data. In this paper, we propose a new algorithm which combines two structures: the incremental breadth-first search, which modifies the Boykov-Kolmogorov algorithm with regard to how it finds a path from the source to the sink of a graph in the max-flow problem in order to help reduce the processing time of the PUMA algorithm; and a pre-filter which operates on the principle of adaptive local denoising. Simulations and experimental implementations were used to demonstrate the ability of the proposed algorithm.