A semi-automatic method for burn scar delineation using a modified Chan-Vese model

Authors:
Yaxin Peng;Ling Pi;Chaomin Shen
Affiliations:
Department of Mathematics, East China Normal University, Shanghai, China and UMPA, ícole Normale Supérieure de Lyon, Lyon, France and CMLA, Ecole Normale Superieure de Cachan, Cachan, Fr ...;Department of Mathematics, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science, East China Normal University, Shanghai 200062, China
Venue:
Computers & Geosciences
Year:
2009

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Abstract

We propose a novel semi-automatic method for burn scar delineation from Landsat imagery using a modified Chan-Vese model. Burn scars appear reddish-brown in band 742 false-colour composite of Landsat 7 images. This property is used in our algorithm to delineate burn scars. Firstly, we visually choose sample pixels from the burn scar. From these pixels, a discrimination function for burn scars is determined by the principal component analysis and interval estimation. Then we define a modified Chan-Vese functional. The minimizer of the functional corresponds to the boundary of the burn scar. In order to minimize this functional, the corresponding contour evolution equation is given. We use the discrimination function to locate an initial contour that is near the boundary of the burn scar. The evolving curve then efficiently converges to the desired boundary. A Landsat image over Russia is used to examine our algorithm. The result shows that the algorithm is effective.