Superresolution reconstruction through object modeling and parameter estimation

1 April 1989

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Acoustics, Speech, and Signal Processing

Vol. 37 (4) , 592-595
https://doi.org/10.1109/29.17545

Abstract

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.

Keywords

This publication has 7 references indexed in Scilit:

High resolution spectral estimation through localized polynomial approximation
Published by Institute of Electrical and Electronics Engineers (IEEE) ,2003
Tomographic Image Reconstruction from Incomplete View Data by Convex Projections and Direct Fourier Inversion
IEEE Transactions on Medical Imaging, 1984
Discrete and continuous band-limited signal extrapolation
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
Estimating the parameters of exponentially damped sinusoids and pole-zero modeling in noise
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1982
Image Restoration by the Method of Convex Projections: Part 1ߞTheory
IEEE Transactions on Medical Imaging, 1982
Image reconstruction from incomplete and noisy data
Nature, 1978
A new algorithm in spectral analysis and band-limited extrapolation
IEEE Transactions on Circuits and Systems, 1975