The iterative convolution–thresholding method (ICTM) for image segmentation
作者：
Highlights：
• A new method is proposed for minimizing general objective functionals for image segmentation.
• The method is based on the representation of segments via characteristic functions.
• The method simply alternates two steps: convolution and thresholding.
• The algorithm has the optimal complexity O(NlogN) per iteration and fast convergence.
• The monotone decay of the objective functional is rigorously proved.
摘要
•A new method is proposed for minimizing general objective functionals for image segmentation.•The method is based on the representation of segments via characteristic functions.•The method simply alternates two steps: convolution and thresholding.•The algorithm has the optimal complexity O(NlogN) per iteration and fast convergence.•The monotone decay of the objective functional is rigorously proved.
论文关键词：Convolution,Thresholding,Image segmentation,Heat kernel
论文评审过程：Received 14 April 2020, Revised 17 April 2022, Accepted 13 May 2022, Available online 14 May 2022, Version of Record 18 May 2022.
论文官网地址：https://doi.org/10.1016/j.patcog.2022.108794
