Phase denoising and unwrapping method for moiré fringes based on multiresolution analysis

Phase unwrapping for moiré fringes plays a crucial role in moiré tomography, and the precision of its outcomes deeply influences the detection results concerning high-temperature complex flow fields. In this paper, a phase denoising and unwrapping technique grounded in multiresolution analysis (MRA) is presented, and it is effectively applied to extract phase information from moiré fringes for propane-air flame and argon arc plasma flow fields. Firstly, the wrapped phase undergoes a wavelet packet decomposition for overall denoising. Subsequently, MRA is conducted to refine the denoising process and unwrap phase, involving layered wavelet packet decomposition and iterative unwrapping on different levels of approximate components. Following the hierarchical structure of MRA, the results from different levels are systematically combined and summarized. In order to ascertain the feasibility and applicability of this approach, a comparison is conducted between the results obtained from our proposed method and those obtained from three representative traditional methods. And then, the outcomes obtained from various unwrapping methods in scenarios involving noise and discontinuity, as well as the results between diverse wavelet basis functions, different decomposition layers and distinct iterations, are meticulously analyzed and compared. The findings indicate that our proposed method outperforms traditional phase unwrapping techniques in terms of continuity and smoothness, particularly when exposed to severe noise. Unlike the three classic methods, our proposed method maintains consistent results even in the presence of noise, thereby highlighting its advantages in terms of resilience against noise. In a word, this research serves as a crucial reference for the accurate detection of complex high-temperature flow fields by moiré tomography.