Active contours driven by median global image fitting energy for SAR river image segmentation |
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| Affiliation: | 1. School of Automation, Northwestern Polytechnical University, Youyi West Road No. 127, Shanxi, Xi’an, 710072 China;2. Department of Computing Science, University of Alberta, Edmonton, Alberta, T6G 2E8 Canada;3. The Institute of Artificial Intelligence and Robotic, Xi’an Jiaotong University, Xianning West Road No. 28, Shanxi, Xi’an, 710049 China;4. National Key Laboratory of UVA Technology, Northwestern Polytechnical University, Youyi West Road No. 127, Shanxi, Xi’an, 710072 China;1. School of Mechanical and Electric Engineering, Soochow University, No. 178, Ganjiang Road, Suzhou, Jiangsu 215021, China |
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| Abstract: | The existing active contour models can not achieve accurate segmentation of SAR river images. To solve this difficulty, a novel active contour model driven by median global image fitting energy is proposed. First, the median global fitted image is defined. Then by minimizing the difference between the median global fitted image and the original image, the energy functional of the proposed model is obtained. Moreover, the within-cluster absolute differences of the pixel grayscale values inside and outside the curve are introduced to adaptively adjust the proportions of the region energies inside and outside the curve. Compared with the popular active contour models, extensive experimental results demonstrate the proposed model has clear advantages in terms of both segmentation performance and segmentation efficiency. |
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| Keywords: | Image segmentation Active contour model Median global image fitting energy Within-cluster absolute difference |
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