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Defogging computational ghost imaging via eliminating photon number fluctuation and a cycle generative adversarial network

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Imaging through fluctuating scattering media such as fog is a challenge since it seriously degrades the image quality. Here, we investigated how the image quality of computational ghost imaging is… Click to show full abstract

Imaging through fluctuating scattering media such as fog is a challenge since it seriously degrades the image quality. Here, we investigated how the image quality of computational ghost imaging is reduced by fluctuating fog and how to obtain a high-quality defogging ghost image. We show theoretically and experimentally, that the photon number fluctuations introduced by fluctuating fog is the reason for ghost image degradation. An algorithm is proposed to process the signals collected by the computational ghost imaging device to eliminate photon number fluctuations of different measurement events. Thus, a high-quality defogging ghost image is reconstructed even though fog is evenly distributed on the optical path. A nearly 100% defogging ghost image is obtained by further using a cycle generative adversarial network to process the reconstructed defogging image.

Keywords: photon number; ghost imaging; ghost; computational ghost; image

Journal Title: Chinese Physics B
Year Published: 2023

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