River channel extraction from synthetic aperture radar images based on region-based active contour model

Abstract

River channel extraction is an active and challenging task in many applications, for improving the accuracy and efficiency of river channel extraction, and the paper presents a region-based active contour model, which is driven by the logarithm kernel-based energy function. Firstly, the regional energy function is defined by the logarithm kernel distance which is robust and non-Euclidean. Secondly, the local median information of image is considered rather than global image statistics to reduce the influence of intensity inhomogeneity presented in each region. Furthermore, the interior and exterior energies are calculated by the variation which integrates each pixel with fitting center. Finally, the distance regularized term is introduced to avoid re-initialization of the level set function. Experimental results show that, comparing with other state-of-the-art models, the proposed model can be applied to synthetic aperture radar river channel extraction with desirable results.