[IPOL announce] new article: PALMS Image Partitioning Lab - A Toolbox for Image Partitioning with the Piecewise Affine-Linear Mumford-Shah Model

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2020/295/

Lukas Kiefer, Martin Storath, and Andreas Weinmann,
PALMS Image Partitioning Lab - A Toolbox for Image Partitioning with the 
Piecewise Affine-Linear Mumford-Shah Model, Image Processing On Line, 10 
(2020), pp. 124–149.
https://doi.org/10.5201/ipol.2020.295

Abstract
We present a method for computing approximate solutions of the piecewise 
affine-linear Mumford-Shah model - PALMS Image Partitioning. The 
piecewise affine-linear Mumford-Shah model is a variational approach to 
image partitioning. The underlying algorithm is based on a splitting 
approach using ADMM. The emerging subproblems are solved exactly and 
efficiently. We detail the solver for these subproblems which is based 
on dynamic programming and incorporates an acceleration strategy. The 
subproblems are solved in parallel in our implementation to provide an 
efficient overall algorithm. We conduct extended studies on the effects 
of the algorithmic parameters. Thereby, the implemented algorithm is 
further optimized w.r.t. runtime and efficiency. Finally, we underpin 
the efficiency of the algorithm by a comparison with the 
state-of-the-art which shows that the presented algorithm has lower 
computation times and yields lower mean functional values.