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Parametric modeling of blurred images for image restoration

Conference Paper


Abstract


  • Almost all of parameter estimation schemes for image restoration to date, attempt to model the true image as a autoregressive model and the point spread function as a moving average model and assume the symmetry of the point spread function in order to reduce the computational complexity. Autoregressive process builds the true image by passing a Gaussian white noise process through a filter and may result in unstable systems and optimization of parameters could be trapped in local minima. In this article a different approach is presented with simulation results where initial white Gaussian process is replaced by scaled degraded image avoiding optimization problems.

Publication Date


  • 2000

Citation


  • Premaratne, P., & Ko, C. C. (2000). Parametric modeling of blurred images for image restoration. In Conference Record of the Asilomar Conference on Signals, Systems and Computers Vol. 2 (pp. 1727-1730).

Scopus Eid


  • 2-s2.0-0034442928

Start Page


  • 1727

End Page


  • 1730

Volume


  • 2

Abstract


  • Almost all of parameter estimation schemes for image restoration to date, attempt to model the true image as a autoregressive model and the point spread function as a moving average model and assume the symmetry of the point spread function in order to reduce the computational complexity. Autoregressive process builds the true image by passing a Gaussian white noise process through a filter and may result in unstable systems and optimization of parameters could be trapped in local minima. In this article a different approach is presented with simulation results where initial white Gaussian process is replaced by scaled degraded image avoiding optimization problems.

Publication Date


  • 2000

Citation


  • Premaratne, P., & Ko, C. C. (2000). Parametric modeling of blurred images for image restoration. In Conference Record of the Asilomar Conference on Signals, Systems and Computers Vol. 2 (pp. 1727-1730).

Scopus Eid


  • 2-s2.0-0034442928

Start Page


  • 1727

End Page


  • 1730

Volume


  • 2