Image Restoration By Spatial Filter Design

Abstract

A variety of techniques are present for restoration of images. One of the powerful techniques is Wiener filtering. Performing Fourier tranforms on an image processor for large multi-spectral images involves enormous computational effort. The problem considered here is a way of designing small spatial filters that approximate their frequency domain counterparts so that they can be implemented easily. Such a filter is very useful, particularly if the point spread function affecting different images or different bands of a multi-spectral image can be considered the same. It is also useful if a filter , designed for one section of a large image, can be applied to the entire image. It is a particularly valuable method in a production environment. An example of this is removal of atmospheric effects in satellite images. The objective of this paper is to show that such spatial filters can be very effective, a way to design them and how they are implemented on a commercially available image processor. The limitations of this technique are also discussed. Examples are shown on restoration of atmospherically degraded Landsat Thematic Mapper images.