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Capturing depth and reflectivity images at low light levels from active illumination of a scene has wide-ranging applications. Conventionally , even with single-photon detectors, hundreds of photon detections are needed at each pixel to mitigate Poisson noise. We introduce a robust method for estimating depth and reflectivity using on the order of 1(More)
—In conventional 3D imaging, a large number of detected photons is required at each pixel to mitigate the effect of signal-dependent Poisson or shot noise. Parametric Poisson process imaging (PPPI) is a new framework that enables scene depth acquisition with very few detected photons despite significant contribution from background light. Our proposed(More)
Range estimation at low light-levels is accomplished using pulsed illumination of the target and time-of-flight measurement of backscat-tered light using single-photon detectors. Photon arrival statistics for this problem are time-inhomogeneous Poisson point processes where the rate function is determined by the illumination waveform. Given the flexibility(More)
Multiplexed imaging is a powerful mechanism for achieving high signal-to-noise ratio (SNR) in the presence of signal-independent additive noise. However, for imaging in presence of only signal-dependent shot noise, multiplexing has been shown to significantly degrade SNR. Hence, multiplexing to increase SNR in presence of Poisson noise is normally thought(More)
Reconstructing a scene's 3D structure and reflectivity accurately with an active imaging system operating in low-light-level conditions has wide-ranging applications, spanning biological imaging to remote sensing. Here we propose and experimentally demonstrate a depth and reflectivity imaging system with a single-photon camera that generates high-quality(More)
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