In recent years, the development of quanta image sensor (QIS), which can observe the amount of incident light intensity in units of photons, has been progressing. In QIS imaging, a large number of photon incident observations are performed in spatiotemporal direction, and multivalued images are obtained by reconstruction processing. In this observation, the binary value is output according to whether the number of incident photons exceeds a certain natural number of threshold preset in the minute photon detector (jot). In many existing methods for QIS imaging, a uniform threshold is set for all jots, the reconstructed multivalued image may be overexposed or underexposed. On the other hand, the method of setting an optimal threshold for each local region according to the scene requires time for adjustment, which leads to a decrease in temporal resolution. In this paper, we propose an imaging method that always accurately captures a wide range of light intensity from low to high by introducing a periodic pattern consisting of multiple thresholds. Since we do not adjust the threshold according to the scene, we can fundamentally avoid the degradation of temporal resolution. In addition, since the threshold applied to jots has a variety of values, it is possible to acquire a high-quality multivalued image even with a small number of photon incident observations. Our proposed method consists of three components: multivalued image reconstruction and noise reduction taking into account the characteristics of photon incident observation, and optimization of the periodic pattern.


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    Title :

    Imaging method using multi-threshold pattern for photon detection of quanta image sensor


    Contributors:

    Conference:

    International Workshop on Advanced Imaging Technology (IWAIT) 2022 ; 2022 ; Hong Kong,China


    Published in:

    Proc. SPIE ; 12177


    Publication date :

    2022-04-30





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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