A level set method based on additive bias correction for image segmentation
作者：
Highlights：
• The proposed additive bias correction theory define the local clustering criterion.
• The local and global clustering criterion is computed based on level set method.
• The bias field and reflection edge are computed through minimizing energy function.
• A new de-parameterized regularization function and adaptive function are designed.
• The proposed model shows better segmentation speed and accuracy.
摘要
•The proposed additive bias correction theory define the local clustering criterion.•The local and global clustering criterion is computed based on level set method.•The bias field and reflection edge are computed through minimizing energy function.•A new de-parameterized regularization function and adaptive function are designed.•The proposed model shows better segmentation speed and accuracy.
论文关键词：Image segmentation,Intensity inhomogeneity,Additive bias correction,Reflectance image,Level set method
论文评审过程：Received 24 November 2020, Revised 4 May 2021, Accepted 18 July 2021, Available online 26 July 2021, Version of Record 30 July 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115633
