A phase recovery detection system for intermediate frequency errors of optical components enhanced by convolutional neural network prior

Abstract

The invention discloses a phase recovery detection system for intermediate frequency errors of optical elements enhanced by convolutional neural network priori. A calibrated spatial light modulator is used to generate phase modulation of intermediate frequency errors, and the modulated light is projected onto an imaging camera for reception. In order to obtain multiple sets of data pairs of intensity patterns and intermediate frequency error description items, as the training data set of the neural network, and then use the trained model to detect the real intermediate frequency error; compared with the data obtained by simulation, the system provides The model trained by the data is more suitable for recovering the actual intermediate frequency error; the invention realizes the initial solution optimization of the phase recovery intermediate frequency error detection technology; the convolutional neural network model in deep learning is used to establish the intensity pattern after the intermediate frequency error modulation and The relationship between the error distribution can predict the phase distribution of the intermediate frequency error, and the result is used as the initial solution of the phase recovery algorithm, which effectively improves the convergence performance of the algorithm and increases the convergence speed.

Description

technical field [0001] The invention relates to a priori enhanced intermediate frequency error phase recovery detection system in the field of computational imaging, in particular to a convolutional neural network priori enhanced optical element intermediate frequency error phase recovery detection system. Background technique [0002] Optical components with large aperture and small F number are widely used in high-power laser systems such as inertial confinement fusion, and these systems have higher requirements for the surface quality of optical components. However, in the process of precision machining and polishing of optical components, due to the tip radius of the processing tool, processing method, vibration and thermal drift, etc., a periodic structure with a certain frequency will be left on the surface of the component, which is called the surface of the optical component. Errors, the existence of these surface errors will have a significant impact on the transmis...

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Problems solved by technology

[0004] However, during the operation of its iterative algorithm, the phase recovery technology often cannot correctly converge to the global optimal solution, but stagnates at the local minimum, which makes the surface shape results obtained by the detection system less accurate

In addition, when the initial solution of the surface error does not have sufficient prior information, the calculation process of the phase recovery detection system often takes too long to run, and sometimes even fails to converge

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