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Proceedings Paper

Detail-preserving solution to the problem of shoreline detection in remotely sensed images
Author(s): Giancarlo Bo; Silvana G. Dellepiane; Fabrizio Giorgini; Maurizio Bartolini
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Paper Abstract

A technique for the detection of the shoreline in remotely sensed images will be presented. The proposed technique is based on the involvement of the local contextual information, which is always present in remotely sensed data. In a previous version of the method a connectivity map was computed by exploiting the gray levels and the physical distance between pixels in the image. The results obtained by processing different kinds of remotely sensed data clearly show that it is possible to correctly detect the shoreline position only if the sea portion is really homogeneous. Problems arises when sources of non-homogeneity are present in the image. An improved version of the method has been implemented, which exploits texture features, instead of the simple gray level, in order to compute the connectivity map. By operating in this way it is possible to better take into account the spatial variability of data as an information source. It is important to underline that the described technique is intrinsically independent from the specific spatial resolution of data, then it applies to any kind of images. This means that the approach, though already useful for upgrading coastal databases or for cartographic applications, could be usefully employed for erosion or accretion monitoring and geomorphologic analysis when images characterized by a higher resolution will be available.

Paper Details

Date Published: 19 January 2001
PDF: 10 pages
Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); doi: 10.1117/12.413910
Show Author Affiliations
Giancarlo Bo, Univ. of Genoa (Italy)
Silvana G. Dellepiane, Univ. of Genoa (Italy)
Fabrizio Giorgini, Univ. of Genoa (Italy)
Maurizio Bartolini, Univ. of Genoa (Italy)

Published in SPIE Proceedings Vol. 4170:
Image and Signal Processing for Remote Sensing VI
Sebastiano Bruno Serpico, Editor(s)

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