Solving effectively nonlinear optimization is a key step in image processing, especially in variational modeling. While gradient descent methods and augmented Lagrangian methods operating on a single mesh level are popularly used, developing fast and optimal multilevel methods are of great importance. This talk extends previous works on multilevel methods for image restoration to image segmentation where there is a further scope to explore in acceleration beyond $O(N\ln N)$ complexity.

This presentation is part of Minisymposium “MS49 - Image Restoration, Enhancement and Related Algorithms (4 parts)”
organized by: Weihong Guo (Case Western Reserve University) , Ke Chen (University of Liverpool) , Xue-Cheng Tai (Hong Kong Baptist University) , Guohui Song (Clarkson University) .

Authors:

Ke Chen (University of Liverpool)

Abdul Jumaat (University of Liverpool)

Keywords:

image segmentation, nonlinear optimization, numerical linear algebra