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- W2517388314 abstract "Quanta Image Sensor (QIS) has been envisioned as a candidate solution for next generation image sensors. We provide two new contributions to the signal processing aspects of QIS. First, we develop an image reconstruction algorithm to recover the underlying images from the QIS data, which is a massive array of binarized Poisson random variables. The new algorithm supersedes existing methods by enabling arbitrary threshold level. Second, we present a threshold design scheme to adaptively update the threshold level for optimal image reconstruction. We discuss the existence of a phase transition in determining the optimal threshold. Experimental results on tone-mapped high dynamic range images validates the effectiveness of the threshold scheme and the image reconstruction algorithm." @default.
- W2517388314 created "2016-09-16" @default.
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- W2517388314 date "2016-09-01" @default.
- W2517388314 modified "2023-09-26" @default.
- W2517388314 title "Image reconstruction and threshold design for Quanta Image Sensors" @default.
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- W2517388314 doi "https://doi.org/10.1109/icip.2016.7532503" @default.
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