Inversion of Atmospheric Turbulence Strength by Neural Network Based on Mixed-domain Attention Mechanism
A neural network method based on the mixed-domain attention mechanism is proposed to invert the atmospheric turbulence strength.The input of the neural network is the degraded images under different atmospheric turbulence strengths,and the output is the refractive index structure constant that characterises the atmospheric turbulence strength.The mixed-domain attention mechanism consists of dual spatial-domain and channel-domain attention mechanisms,where the spatial-domain attention mechanism is used to enhance turbulence-affected region features in the degraded image,and the channel-domain attention mechanism is used to enhance turbulence-induced colour and texture features.In the network training stage,the introduced mixed-domain attention mechanism allows the neural network to focus more on the features in the degraded image that are related to the atmospheric turbulence strength,which improves the accuracy of the model.Numerical experimental results show that the method proposed in this paper can achieve atmospheric turbulence strength inversion more accurately.
mixed-domain attention mechanismrefractive index structure constantturbulence strength inversiondegraded image
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