Edge discrimination as applied to Thematic Mapper data

Abstract

An evaluation of suitable edge discrimination techniques and their application to image segmentation is reported. From an analysis of Thematic Mapper Simulator data, it is concluded that segmentation by automated edge discrimination is a valuable technique which can be used in the development of per-field classifiers. A Laplacian convolution operator appears to be the most cost-effective high-pass filter. Spatial frequency domain filtering is more versatile in its ability to enhance different edge types. A simple global gray value threshold can produce good edge discrimination from an enhanced image which may be improved by using a local thresholding technique. A gap-fill postprocessing technique is necessary for useful segmentation. Gradient and other directionally dependent techniques are unsuitable for segmentation.