A versatile algorithm for two-dimensional symmetric noncausal modeling

In this work a novel algorithm is presented for the efficient two-dimensional (2-D) symmetric noncausal finite impulse response (FIR) filtering and autoregressive (AR) modeling. Symmetric filter masks of general boundaries are allowed. The proposed algorithm offers the greatest maneuverability in the 2-D index space in a computationally efficient way. This flexibility can be taken advantage of if the shape of the 2-D mask is not a priori known and has to be dynamically configured.