Uniformly minimum variance unbiased estimation for asynchronous event-based cameras

Asynchronous event-based cameras use time encoding to code the pixel intensity values. A time encoding of a random valued pixel is a representation of the intensity of this pixel as a random sequence of strictly increasing times. The goal of this paper is the estimation of the pixel mean value from asynchronous samples given by the integrate and fire time encoding. The optimal uniformly minimum variance unbiased estimator is calculated and its statistical performance is compared with a conventional frame-based estimator which exploits regular samples of the pixel intensity. Time encoding significantly reduces the mean number of bits needed to minimize the mean square error of the estimate. Hence, time encoding saves power compared to regular sampling.

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