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In this paper, we present results achieved at ISL that demonstrate how single-photon imaging combined with computational methods differs from classical imaging methods. We show how we can extract and reconstruct new, previously unattainable information from scenes. ISL has investigated passive single photon counting to reconstruct the photon flux imaging the sensor array. We could reconstruct image information and obtained up-scaling by application of convolutional neural networks, reduced noise and motion blur by computer vision algorithms. Finally, we extracted modulation frequencies by Fourier analysis and obtained event-based neuromorphic imaging. Further, we have studied laser-based active imaging of single photons to measure the round-trip path length of light pulses for ranging and 3D imaging. We have analyzed multi-bounce photon path to estimate the size of cavities and to improve vision through scattering media such as dense fog. Finally, we investigated SPAD sensing for the reconstruction of objects outside the direct line of sight in non-line of sight (NLOS) sensing approaches. |
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