SE-FSCNet: full-scale connection network for single-shot phase demodulation

Abstract

The accuracy of phase demodulation has significant impact on the accuracy of fringe projection 3D measurement. Currently, researches based on deep learning methods for extracting wrapped phase mostly use U-Net as the subject of network. The connection method between its hierarchies has certain shortcomings in global information transmission, which hinders the improvement of wrapped phase prediction accuracy. We propose a single-shot phase demodulation method for fringe projection based on a novel full-scale connection network SE-FSCNet. The encoder and decoder of the SE-FSCNet have the same number of hierarchies but are not completely symmetrical. At the decoder a full-scale connection method and feature fusion module are designed so that SE-FSCNet has better abilities of feature transmission and utilization compared with U-Net. A channel attention module based on squeeze and excitation is also introduced to assign appropriate weights to features with different scales, which has been proved by the ablation study. The experiments conducted on the test set have demonstrated that the SE-FSCNet can achieve higher precision than the traditional Fourier transform method and the U-Net in phase demodulation.