What is Realised kernel, pre-averaging estimator?

A realised kernel (Barndorff-Nielsen, Hansen, Lunde and Shephard, 2008) adds weighted autocovariances of the high-frequency returns to their variance, $\gamma_0 + \sum_{h=1}^Hk\bigl(\frac{h-1}H\bigr)(\gamma_h + \gamma_{-h})$, with a smooth weight such as Parzen’s, to cancel the negative autocovariance the noise creates. The pre-averaging estimator (Jacod, Li, Mykland, Podolskij and Vetter, 2009) averages returns over short overlapping windows with a weight function, which shrinks the noise in each window, then squares and rescales the averages and subtracts the remaining bias.