Superresolution reconstruction through object modeling and parameter estimation

A method based on object modeling and parameter estimation is proposed to achieve superresolution reconstruction. An efficient method for solving for the model parameters is given that uses linear prediction theory and linear least squares fitting. Reconstruction results from simulated and real magnetic resonance data are also presented to demonstrate its capability for Gibbs ringing reduction and resolution enhancement.<>