摘要
It is of great difficulty to utilize the existing active contour models (ACMs) to achieve accurate segmentation of synthetic aperture radar (SAR) river images. To address this problem, a novel ACM driven by J-divergence entropy is proposed. The external energy constraint term of the proposed model is defined by the J-divergence entropy, which differs from those of many existing ACMs defined by the Euclidean distance. Moreover, the median absolute deviations of pixel grayscale values inside and outside the curve are utilized as energy weights, which can adaptively adjust proportions of region energies inside and outside the curve, leading to the improvement in segmentation efficiency. Experiments are performed on a large number of SAR river images, and the results demonstrate that, compared with the existing ACMs, the proposed model shows clear advantages in terms of both segmentation performance and segmentation efficiency.
- 出版日期2018-8
- 单位长江水资源保护科学研究所; 长江水利委员会长江科学院; 哈尔滨工业大学; 黄河水利委员会黄河水利科学研究院; 城市水资源与水环境国家重点实验室; 南京航空航天大学