Generative adversarial network based single pixel imaging
Single pixel imaging can reconstruct two-dimensional images of a scene with only a single-pixel detector. It has been widely used for imaging in non-visible bandwidth (e.g., near-infrared and X-ray) where focal-plane array sensors are challenging to be manufactured. In this paper, we propose a generative adversarial network based reconstruction algorithm for single pixel imaging, which demonstrates efficient reconstruction in 10ms and higher quality. We verify the proposed method with both synthetic and real-world experiments, and demonstrate a good quality of reconstruction of a real-world plaster using a 0.05 sampling rate.
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