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\documentstyle{article}
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\textheight 9.5in
\textwidth 5.75in
\voffset -1in
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%\documentstyle[12pt]{llncs}
\title{Regularized Bind Deconvolution using Recursive inverse Filtering}
%\author{Michael K. Ng\inst{1}, Robert J. Plemmons\inst{2}, Sanzheng Qiao
%\inst{3}}
%\institute{Computer Sciences Laboratory, The Australian National University,
%\\ Canberra, ACT 0200, Australia
%\and
%Department of Mathematics and Computer Science, \\ Wake Forest University,
%Winston-Salem, NC 27109, USA 
%\and
%Department of Computer Science and Systems, McMaster University, \\
%Hamilton, Ontario L8S 4K1, Canada 
%}
\author{Michael K. Ng \\
Computer Sciences Laboratory, The Australian National University,
\\ Canberra, ACT 0200, Australia
\and
Robert J. Plemmons \\
Department of Mathematics and Computer Science, \\ Wake Forest University,
Winston-Salem, NC 27109, USA
\and
Sanzheng Qiao \\
Department of Computer Science and Systems, McMaster University, \\
Hamilton, Ontario L8S 4K1, Canada
}


\begin{document}
\date{}
\maketitle


Classical image restoration involves the removal or minimization of 
degradation (or blur) in an image using a priori knowledge about the 
degradation phenomena. Blind deconvolution is the process of estimating
both the true image and the blur from the degraded image characteristics,
using partial information about the image system. ...



\end{document}
bob plemmon
