Boundary value problem in image restoration
Recursive spatial domain filtering is often used in image restoration. The techniques range from deterministic inverse filter algorithms [1] to stochastic Kalman filters [2,3]. However, all the techniques have in common the problem of choosing the appropriate boundary values. It is the purpose of this paper to demonstrate the importance of the boundary values in image restoration and to show how we can improve the transient response of the steady-state Kalman filters in [2] and [3] with better choices for the boundary values.