Title :
Simultaneous iterative image restoration and evaluation of the regularization parameter
Author :
Kang, M.G. ; Katsaggelos, A.K.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Northwestern Unv., Evanston, IL, USA
fDate :
9/1/1992 12:00:00 AM
Abstract :
A nonlinear regularized iterative image restoration algorithm is proposed, according to which only the noise variance is assumed to be known in advance. The algorithm results from a set theoretic regularization approach, where a bound of the stabilizing functional, and therefore the regularization parameter, are updated at each iteration step. Sufficient conditions for the convergence of the algorithm are derived and experimental results are shown
Keywords :
convergence of numerical methods; iterative methods; picture processing; random noise; additive white Gaussian noise; algorithm convergence; experimental results; noise variance; nonlinear regularized iterative image restoration algorithm; parameter evaluation; regularization parameter; stabilising functional bound; theoretic regularization approach; Bars; Hardware; Image restoration; Interpolation; Music; Performance evaluation; Psychology; Speech coding; Testing; Timbre;
Journal_Title :
Signal Processing, IEEE Transactions on
