Abstract

For remote sensing with computational ghost imaging, the atmospheric turbulence will influence much on the performance since the transmitted patterns from the pseudo-thermal source will be distorted. As the distribution of refractive index on the propagation path varies with time, reducing the time consumption of data acquisition will be an effective way for mitigating the influence. We propose using fewer pixels of spatial light modulator to increase the modulation rate of the pseudo-thermal source, with the positions of pixels being randomly distributed. Multi-bucket detectors are employed for further reducing of the data acquisition time. The sparse recovery algorithm from compressed sensing is employed to enhance the quality of image. The performance of this system is demonstrated by comprehensive numerical analyses.

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