Nonlinear image restoration using recurrent radial basis function network
For nonlinear distorted images, the performance of the existing image restoration methods is limited in either visual quality or computational complexity. In this paper, we apply the recently developed technique called recurrent radial basis function network (RBFN) for nonlinear image restoration. We give the details of the construction of the recurrent RBFN network and the determination of the network parameters. Simulation results show that the proposed recurrent RBFN scheme outperforms the existing RBFN based methods in both visual quality and complexity when the degraded process is recursive.