An adaptive weighting parameter estimation between local and global intensity fitting energy for image segmentation |
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| Affiliation: | 1. School of Mathematical Sciences/Institute of Computational Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;2. Department of Mathematics and Computer Science, Anshun University, Anshun, Guizhou 561000, PR China;1. School of Mathematics and Information Science, Yantai University, Yantai 264005, Shandong, PR China;2. School of Mathematics and Information Science, Shandong Institute of Business and Technology, Yantai 264005, Shandong, PR China |
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| Abstract: | ![]()
Local and global intensity fitting energy are widely used for image segmentation. In order to improve the segmentation quality in the presence of intensity inhomogeneity, in this paper, we propose a new adaptive rule for obtaining weighting parameter estimation between the local and global intensity fitting energy. Following the minimization of the energy functional, the value of the weighting parameter is dynamically updated with the contour evolution, which is effective and accurate for extracting the object. |
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| Keywords: | Image segmentation Intensity inhomogeneity Level set method Chan–Vese model LBF model |
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