32,348 research outputs found

    Photon-Efficient Computational 3D and Reflectivity Imaging with Single-Photon Detectors

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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 develop a robust method for estimating depth and reflectivity using on the order of 1 detected photon per pixel averaged over the scene. Our computational imager combines physically accurate single-photon counting statistics with exploitation of the spatial correlations present in real-world reflectivity and 3D structure. Experiments conducted in the presence of strong background light demonstrate that our computational imager is able to accurately recover scene depth and reflectivity, while traditional maximum-likelihood based imaging methods lead to estimates that are highly noisy. Our framework increases photon efficiency 100-fold over traditional processing and also improves, somewhat, upon first-photon imaging under a total acquisition time constraint in raster-scanned operation. Thus our new imager will be useful for rapid, low-power, and noise-tolerant active optical imaging, and its fixed dwell time will facilitate parallelization through use of a detector array.Comment: 11 pages, 8 figure

    The stabilisation of the Nx phase in mixtures

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    The phase behaviour of mixtures between two symmetric dimers, CBC9CB and the ether-linked analogue CBOC9OCB was investigated by Polarizing Optical Microscopy (POM), Differential Scanning Calorimetry (DSC) and X-Ray Diffraction (XRD) studies. The dimeric constituents are fully miscible and the construction of a temperature-composition phase diagram reveals a surprising amplification of the stability of the Nx phase in compositions of up to 37 wt% of CBOC9OCB in CBC9CB. The origin for this enhancement of stability is discussed and an explanation based on chiral recognition is developed
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