2-D adaptive CPWQ fast filtering based on weighted least-squares errors

In this paper, a two-dimensional (2-D) fast adaptive filtering algorithm based on the exponentially weighted least squares errors is developed for the non linear canonical piecewise quadratic (CPWQ) model. This algorithm take advantages of the non linear CPWQ modeling and the fast convergence of the exponentially weighted least squares adaptive algorithm. The simulation results show that the proposed method gives good results in image restoration. Experimental comparison with the canonical piecewise linear (CPWL) model shows the superiority of the non linear filter in term of image enhancement.