ABSTRACT

The concept of image restoration differs substantially from the idea of image enhancement. While enhancement aims at improving the appearance of the image or its properties with respect to the following analysis (by a human operator or even automatic), the goal of restoration is to remove an identified distortion from the observed image

g

, thus providing (in a defined sense) the best possible estimate of the original undistorted image

f

. The observed image may be distorted by blur, geometrical deformation, nonlinear contrast transfer, etc., and is usually further degraded by additive or otherwise related noise

. The identification of the properties of distortion (i.e., of the distorting system, the disturbing noise, etc.) therefore forms an essential part of the restoration process. Having described the distortion formally by a mathematical model with measured or estimated parameters, we can try to invert the model and obtain the restored image (estimate of the original) as the result of applying the inverse procedure to the observed (measured, received) image. The schematic representation of the distortion and restoration process is depicted in Figure 12.1.