Structural description of water basins from Landsat imagery using multiscale image relevance function

Conventional methods for cartographic shape representation of objects from satellite images are usually inaccurate and will provide only a rough shape description if they are to work in a fully automated mode. For example, existing algorithms for skeletal thinning fail to provide a correctly shaped skeleton if the input images contain noise or the objects of interest are sparse and exhibit discontinuities. The proposed method for extraction of skeletons of 2-D objects is based on an efficient algorithm for multi-scale structural analysis of images obtained from satellite data. The form and topology of hydrological objects, such as rivers and lakes, can be extracted by applying a multi-scale relevance function in a quick, reliable and scale-independent way. The description of objects is obtained in the form of piecewise linear skeletons (multi-scale structural graph) and includes local scales at graph vertices, which correspond to local maxima of the relevance function. The experimental test results using Landsat-7 images show good accuracy of the relevance function approach and its potential for fully automated hydrographic mapping.