Fuzzy Object Identification Using Texture Based Segmentation Of High-Resolution Dem And Remote Sensing Imagery Of A Coastal Area In England

Introduction Object-oriented approaches to remotely sensed image processing have become increasingly popular with the growing amount of high-resolution satellite and airborne imagery. Several studies have shown that segmentation techniques can help to extract spatial objects from an image. Uncertainty, however, will be present in any segmented image and can have a significant effect on further image processing. In particular, in areas where fuzzy objects dominate an indication of segmentation uncertainty is important. In this study, we present a feature extraction technique that identifies fuzzy objects from remotely sensed imagery of a coastal area in northwest England. This paper builds on work of Lucieer and Stein (2002) and further explores the generation of thematic and spatial object uncertainty in the process of image segmentation.