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In this work we explore the different noise mechanisms in event cameras and discuss known methods for filtering several noise sources. We focus on the threshold mismatch effect in event cameras and introduce a novel correction scheme to reduce the effect of threshold mismatch. To the best of our knowledge this is the first algorithmic solution to the threshold mismatch effect. We use a threshold estimation algorithm suggested by Ziwei Wang et al., and further explore it in simulations with knowledge of the thresholds to calculate estimation errors. Using the estimated thresholds, we apply a correction algorithm based on sampling theory. These methods are tested and evaluated in simulations to provide reference to ground truth for performance evaluation. We also provide insight on performance evaluation and suggest and apply a metric for pixel uniformity.