Target-independent dynamic wavefront sensing method based on distorted grating and deep learning

A real-time wavefront sensing method for arbitrary targets is proposed,which provides an effective way for diversified wavefront sensing application scenarios.By using a distorted grating,the positive and negative defocus images are simultaneously acquired on a single detector.A fine feature,which is independent of the target itself but corresponding to the wavefront aberration,is defined.A lightweight and efficient network combined with an attention mechanism[AM-EffNet]is proposed to establish an accurate mapping between the features and the incident wavefronts.Comparison results show that the proposed method has superior performance compared to other methods and can achieve high-accuracy wavefront sensing in varied target scenes only by using the point target dataset to train the network well.