A Novel Method for Waterline Extraction from Remote Sensing Image Based on Quad-Tree and Multiple Active Contour Model

After the characteristics of geodesic active contour model (GAC), Chan-Vese model (CV) and local binary fitting model (LBF) are analyzed, and the active contour model based on regions and edges is combined with image segmentation method based on quad-tree, a waterline extraction method based on quad-tree and multiple active contour model is proposed in this paper. Firstly , the method provides an initial contour according to quad-tree segmentation; secondly, a new signed pressure force (SPF) function based on global image statistics information of CV model and local image statistics information of LBF model has been defined, and then, the edge stopping function(ESF) is replaced by the proposed SPF function, which solves the problem such as evolution stopped in advance and excessive evolution; finally, the Selective Binary and Gaussian Filtering Level Set method is used to avoid reinitializing and regularization to improve the evolution efficiency. The experimental results show that this method can effectively extract the weak edges and serious concave edges, and owns some properties such as sub-pixel accuracy, high efficiency and reliability for waterline extraction.