A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-norm Fidelity
East China Normal University（华东师范大学）；University of California, Los Angeles（加州大学洛杉矶分校）；Michigan State University（密歇根州立大学）
英文摘要：
In this paper, we propose a variational multiphase image segmentation model based on fuzzy membership functions and L1-norm fidelity. Then we apply the alternating direction method of multipliers to solve an equivalent problem. All the subproblems can be solved efficiently. Specifically, we propose a fast method to calculate the fuzzy median. Experimental results and comparisons show that the L1-norm based method is more robust to outliers such as impulse noise and keeps better contrast than its L2-norm counterpart. Theoretically, we prove the existence of the minimizer and analyze the convergence of the algorithm.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
