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Distributed mixed-signal architecture for programmable smart image sensors

Abstract : Smart vision systems on a chip are promising for embedded applications. Currently, flexibility in the choice of integrated pre-processing tools is obtained at the expense of total silicon area and fill factor, which are otherwise optimized provided that the sensor performs a specific task. We propose a new architecture based on macropixel-level processing to improve the trade-off by using the same processing elements (PEs) for a whole group of pixels. In this paper, we show through transistor-level simulations the feasibility of using macropixel PEs. Their operative part is analog to avoid the bottleneck of analog to digital converters and has digital control which is distributed in and out of the matrix of pixels. PEs are designed to be suitable for coefficient-reconfigurable spatial and temporal filtering. Sharing electronics among several pixels and matching existing algorithms to the target architecture allow for such programmability without degrading too much pixel area nor fill factor.
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Submitted on : Monday, December 3, 2018 - 5:43:59 PM
Last modification on : Thursday, October 6, 2022 - 10:34:31 AM
Long-term archiving on: : Monday, March 4, 2019 - 3:14:16 PM


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Juliette Le Hir, Anthony Kolar, Filipe Vinci dos Santos. Distributed mixed-signal architecture for programmable smart image sensors. Analog Integrated Circuits and Signal Processing, Springer Verlag, 2018, 97 (3), pp.493-501. ⟨10.1007/s10470-018-1342-y⟩. ⟨hal-01943432⟩



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