An Image Segmentation Model with Transformed Total Variation

Code

• github.com/JimTheBarbarian/Official-TTV-Segmentation
  OfficialIn papernone★ 0

Abstract

Based on transformed _1 regularization, transformed total variation (TTV) has robust image recovery that is competitive with other nonconvex total variation (TV) regularizers, such as TV^p, 0<p<1. Inspired by its performance, we propose a TTV-regularized Mumford--Shah model with fuzzy membership function for image segmentation. To solve it, we design an alternating direction method of multipliers (ADMM) algorithm that utilizes the transformed _1 proximal operator. Numerical experiments demonstrate that using TTV is more effective than classical TV and other nonconvex TV variants in image segmentation.

Tasks

Reproductions