Coastline Detection from SAR Images by Level Set Model

Authors:
Maria Mercede Cerimele;Luigi Cinque;Rossella Cossu;Roberta Galiffa
Affiliations:
Istituto per le Applicazioni del Calcolo "M. Picone" CNR, Roma;Universitá degli Studi "Sapienza", Roma;Istituto per le Applicazioni del Calcolo "M. Picone" CNR, Roma;Istituto per le Applicazioni del Calcolo "M. Picone" CNR, Roma
Venue:
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Year:
2009

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Abstract

In this paper we present an innovative and automatic procedure which is used to extract the coastline from SAR (Synthetic Aperture Radar) images by the level set model. This model consists in a PDE (Partial Differential Equation) equation governing the evolution of a curve corresponding to the zero level of a 3D function, called level set function, until the curve reaches the edge of the region to be segmented. A coastline is the boundary between land and sea masses. Detecting the coastline is of fundamental importance when monitoring various natural phenomena such as tides, coastal erosion and the dynamics of glaciers. In this case SAR images show problems which arise from the presence of the speckle noise and of the strong signal deriving from the rough or slight sea. In fact in the case of heavy sea the signal determines an intensity similar to the one of land, making it difficult to distinguish the coastline.