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Real-time anti-turbulence imaging using a diffractive optical processor
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DOI：10.1016/j.optlaseng.2024.108810.png)
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摘要
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The high computational cost and large latency pose great challenges to traditional adaptive optics which correct the distorted wavefront caused by turbulence of the past but not the current state because the loading of compensation information lags the continuously varying distorted wavefront, and thus hindering fast imaging against turbulence. Here, a diffractive optical processor (DOP) capable of real-time imaging of objects from the complex amplitude optical field (CAOF) distorted by atmospheric turbulence is proposed towards tackling the above problems. The DOP only consists of a pair of specifically designed diffractive encoder and decoder. The encoder modulates the distorted object optical field into a Gaussian-shaped intensity distribution and then the decoder recovers the distortion-eliminated object image from this intermediate field. Once trained, the parameters of the diffractive encoder and decoder are fixed and collectively form a passive diffractive processer, positioned between the distorted object optical field and the receiver, enabling adaptive imaging against turbulence at the speed of light. The simulation and experimental results demonstrate that the DOP model shows remarkable imaging performance and generalization ability on both familiar and unfamiliar objects under known and unknown turbulent distortions in the visible wavelength regime. The anti-turbulence imaging on dynamic objects in experiments also intuitively illustrates the real-time performance of the model. Our lightweight DOP is expected to provide strong support for the development of real-time, low-power-consumption adaptive optical imaging systems, and may promise applications in optical remote sensing, astronomical observation, and other fields.
Keyword:
Anti-turbulence
Real-time imaging
Diffractive optical processor
Optical diffraction computing
Optimized training
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3.7
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被引数:
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