A modified GAC model for extracting waterline from remotely sensed imagery

ABSTRACT

At present many methods are available for extracting waterline automatically from remotely sensed imagery. They are commonly limited by their inability to accurately detect waterline when the land–sea interface is not so distinctive on the imagery. This study aims to develop a new model of extraction in which both the spectral features of water and the spatial feature of waterline itself are incorporated into the level set framework. This model consists of three terms. The first term, which is derived from the spectral features, drives the curve evolution. The second term, curvature flow, guarantees the smoothness of the curve in the process of evolution. The third term, the boundary attraction force, attracts the evolving curve to the genuine position. Experimental results with Landsat Thematic Mapper (TM) data sets validate the effectiveness of the proposed model. It can improve the accuracy of extracted waterline and effectively prevent the omission of weak boundaries from the detected results that are common in both geodesic active contour (GAC) and distance-regularized level set evolution (DRLSE) results.

Acknowledgements

We are indebted to East China Normal University for supplying the waterline results derived from manual interpretation by experts. This research is supported financially by the National Natural Science Foundation of China (Grant No. 41174164, 61473310, 41275029), and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported financially by the National Natural Science Foundation of China [grant numbers 41174164, 61473310, and 41275029]; and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.