PALMS Image Partitioning Lab - A Toolbox for Image Partitioning with the Piecewise Affine-Linear Mumford-Shah Model
Lukas Kiefer, Martin Storath, Andreas Weinmann
⚠ This is a preprint. It may change before it is accepted for publication.

Abstract

We present a toolbox for computing approximate solutions of the piecewise affine-linear Mumford- Shah model - PALMS Image Partitioning Lab. 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 incorporate an acceleration strategy. The subproblems can be solved in parallel which our implementation makes use of 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 compar- ison with the state-of-the-art which shows that the presented algorithm has lower computation times and yields lower mean functional values.

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