An Efficient Iterative Thresholding Method for Image Segmentation

This repository contains source code useful for reproducing results presented in the paper An Efficient Iterative Thresholding Method for Image Segmentation (JCP 2017):

@article{WANG2017657,
title = {An efficient iterative thresholding method for image segmentation},
journal = {Journal of Computational Physics},
volume = {350},
pages = {657-667},
year = {2017},
issn = {0021-9991},
doi = {https://doi.org/10.1016/j.jcp.2017.08.020},
url = {https://www.sciencedirect.com/science/article/pii/S0021999117305910},
author = {Dong Wang and Haohan Li and Xiaoyu Wei and Xiao-Ping Wang},
keywords = {Iterative thresholding, Image segmentation, Piecewise constant Mumford–Shah functional, Convolution, Fast Fourier transform},
abstract = {We proposed an efficient iterative thresholding method for multi-phase image segmentation. The algorithm is based on minimizing piecewise constant Mumford–Shah functional in which the contour length (or perimeter) is approximated by a non-local multi-phase energy. The minimization problem is solved by an iterative method. Each iteration consists of computing simple convolutions followed by a thresholding step. The algorithm is easy to implement and has the optimal complexity O(Nlog⁡N) per iteration. We also show that the iterative algorithm has the total energy decaying property. We present some numerical results to show the efficiency of our method.}
}