Abstract
A knowledge-based, hierarchical, unsupervised classification scheme for high-resolution multispectral satellite (HRMS) images is described. This scheme, which finds its conceptual bases in the work of Nagao and Matsuyama for structural analysis of aerial photographs, introduces a new filtering algorithm which is able to preserve fine linear structures of the image. An example of the application of this classification scheme to a Landsat Thematic Mapper multispectral image is presented. >
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