River network detection on simulated swot images based on curvilinear denoising and morphological detection

In this paper, a new technique is presented to detect the river networks in simulated SWOT images. The proposed algorithm is based on a noise reduction step followed by a directional morphological filter. In this work, the speckle noise reduction has been achieved by using a Curvelet-based filter preserving the structures of interest. After the filtering task, a river contrast enhancement has been presented by using the Path-Opening filter. This morphological filtering has retained the curvilinear structures on the image independently of their orientation. Hence, the river detection has been possible by a simple thresholding on the Path-Opening result. The obtained results are evaluated using a visual inspection and a quantitative evaluation. The potential of the proposed algorithm has been evaluated by studying the robustness of the parameters.