Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72845
Title: Parametric modeling of blurred images for image restoration
Authors: Premaratne, P.
Ko, C.C. 
Issue Date: 2000
Source: Premaratne, P.,Ko, C.C. (2000). Parametric modeling of blurred images for image restoration. Conference Record of the Asilomar Conference on Signals, Systems and Computers 2 : 1727-1730. ScholarBank@NUS Repository.
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.
Source Title: Conference Record of the Asilomar Conference on Signals, Systems and Computers
URI: http://scholarbank.nus.edu.sg/handle/10635/72845
ISSN: 10586393
Appears in Collections:Staff Publications

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