Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

With the explosive growth of mathematical optimization and computing hardware, deep
neural networks (DNN) have become tremendously powerful tools to solve many …

Phase unwrapping is an indispensable step for many optical imaging and metrology
techniques. The rapid development of deep learning has brought ideas to phase …

In this paper a novel, to the best of our knowledge, deep neural network (DNN), VUR-Net, is
proposed to realize direct and accurate phase unwrapping. The VUR-Net employs a …

Fringe projection profilometry is an effective technique for handheld three-dimensional
shape measurement because of its high resolution and accuracy. However, it is hard to …

This paper proposes applying the nested U^ 2-Net to a two-dimensional phase unwrapping
(PU). PU has been a classic well-posed problem since conventional PU methods are always …

The single-camera system projecting single-frequency patterns is the ideal option among all
proposed Fringe Projection Profilometry (FPP) systems in terms of measurement speed and …

In this paper, we first propose a quantitative indicator to measure the amount of prior
information contained in the wrapped phase map. Then, Edge-Enhanced Self-Attention …

Phase unwrapping is a critical step to obtaining a continuous phase distribution in optical
phase measurements and coherent imaging techniques. Traditional phase-unwrapping …

Phase unwrapping (PhU) is an important step in interferometric synthetic aperture radar
(InSAR) technology. At present, difficulties are encountered when using deep learning to …