Stochastic modelling and 3D minimum variance recursive estimation of imagesequences

In this paper the 3D minimum variance filtering problem is considered. The proposed spatiotemporal filter is derived according to the assumption that the 3D signal can be modelled by an ensemble of smooth 3D gaussian random f ields. The resulting filtering algorithm is given by an optimal combination of three 1D estimators and is endowed with an information on the location about the spatiotemporal discontinuities of the signal. This allows the fil ter to conciliate the two opposite requirements of an effective noise reduc tion and edge preservation.