1997 | OriginalPaper | Buchkapitel
A Hybrid Method for Preprocessing and Classification of SPOT Images
verfasst von : Shan Yu, Konrad Weigl
Erschienen in: Neurocomputation in Remote Sensing Data Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we present a hybrid method for preprocessing and classification of satellite images. The preprocessing consists of computing texture measures of the images and initialising the probabilities of pixels belonging to different land-cover classes. The objective of the preprocessing is twofold: increasing discrimination power and removing irrelevant characteristics. The classification process consists of assigning a class to each pixel, with a special interest in detecting urban areas as completely as possible with the aid of a priori knowledge. This interest stems from the possible requirement of detecting urban areas on satellite images (even small villages in the countryside) while ignoring some classes (such as parks) in cities. We shall show how this requirement is translated into constraints imposed in our classification process. Experimental results are illustrated through a SPOT image containing a coastal town.