SAR River Image Segmentation by Active Contour Model Inspired by Exponential Cross Entropy

Utilizing the existing active contour models to achieve accurate segmentation of SAR river images is ineffective. To address this difficult, a novel active contour model inspired by exponential cross entropy is proposed. The external energy constraint term of the proposed model is defined inspired by exponential cross entropy. Then, the means of the pixel grayscale values inside and outside the curve are utilized to modify the external energy constraint term, which can improve segmentation performance. Moreover, the Dirac function is replaced by the edge magnitude function to accelerate the curve evolution, which can improve segmentation efficiency. The extensive experiments are performed on a large number of SAR river images and the results demonstrate that the proposed model outperforms the existing active contour models in terms of both segmentation performance and segmentation efficiency.