The application of spatial filtering methods to urban feature analysis using digital image data

Abstract

We describe a method of spatial filtering in the frequency domain which enhances edges and boundaries, thus making small urban features such as parks, tree-lined streets and new housing developments, visible on digital images with, for example, 30 m resolution. Hitherto, while satellite imagery has been useful because of its large area and repetitive coverage, the spatial resolution for multiband imagery has been such that it precluded the detailed studies which may now be possible. While spatial frequency filtering, edge enhancement, high-boost and directional filtering have been possible, this has generally involved the use of a convolution matrix whose elements have been defined from general empirical rules. Frequency domain operations offer the advantage of selectively tailoring the filter in order to enhance certain features.