Hierarchy construction schemes within the Scale set framework

TL;DR

This paper investigates how different hierarchy construction schemes within the scale set framework affect optimal segmentation cuts, proposing new sequential and parallel methods that improve efficiency and solution quality.

Contribution

It introduces new sequential and parallel hierarchy construction schemes within the scale set framework, enhancing segmentation quality and computational efficiency.

Findings

Sequential methods yield partitions close to global optima.

Parallel methods are faster than existing approaches on sequential machines.

Proposed methods improve hierarchy construction for energy-based segmentation.

Abstract

Segmentation algorithms based on an energy minimisation framework often depend on a scale parameter which balances a fit to data and a regularising term. Irregular pyramids are defined as a stack of graphs successively reduced. Within this framework, the scale is often defined implicitly as the height in the pyramid. However, each level of an irregular pyramid can not usually be readily associated to the global optimum of an energy or a global criterion on the base level graph. This last drawback is addressed by the scale set framework designed by Guigues. The methods designed by this author allow to build a hierarchy and to design cuts within this hierarchy which globally minimise an energy. This paper studies the influence of the construction scheme of the initial hierarchy on the resulting optimal cuts. We propose one sequential and one parallel method with two variations within both. Our sequential methods provide partitions near the global optima while parallel methods require less execution times than the sequential method of Guigues even on sequential machines.