By Topic

Model-based non-linear estimation for adaptive image restoration

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xiaolin Wu ; Dept. of Electrical & Computer Engineering, McMaster University, Hamilton, Canada L8S 4K1 ; Xiangjun Zhang

We propose a new image restoration algorithm that is driven by an adaptive piecewise autoregressive model (PAR). The strength of the new algorithm is its ability to preserve spatial structures better than its predecessors. The high adaptability is achieved by locally fitting 2D image waveform to the PAR model in moving windows. The problem is posed as one of nonlinear least-square estimation of both PAR parameters and original pixels, constrained by the degradation function. Robust solutions of the underlying underdetermined inverse problem are obtained by an innovative use of multiple PAR models that circumvent the issue of model overfitting, and by applying a structured total least-square technique.

Published in:

2009 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

19-24 April 2009