ABSTRACT
Throughout the past two decades, digital image processing has made its way into today's technology and computer-driven society. Its applications encompass a wide variety of specialized disciplines including medical imaging, machine vision, remote sensing, and astronomy—even influencing the computer user at home. Personal images obtained with digital cameras can easily be manipulated by a variety of dedicated commercial and public domain image-processing software packages. Image restoration has to be defined in this context. While image enhancement strives to bring out certain features in an image to simplify the extraction of image information, image restoration is the attempt to retrieve information that has been lost or obscured in the imaging process itself, thus obtaining a result that is closer to an ideal image of the object. Therefore, image restoration requires a systems approach that takes into account the entire process of image formation including the propagation of light through inhomogeneous media, the properties of the optical system, and the characteristics of the detector. Here, solar astronomy will serve as an example of the image formation process. We will discuss various image restoration methods and the underlying mathematical models.
