A Restricted-Domain Dual Formulation for Two-Phase Image Segmentation
This is an incremental improvement for researchers and practitioners in image segmentation, offering a potentially more efficient alternative for similar problems.
The paper tackles the computational efficiency problem in two-phase image segmentation by solving a dual formulation in a restricted domain, resulting in quantified improvements in computational performance.
In two-phase image segmentation, convex relaxation has allowed global minimisers to be computed for a variety of data fitting terms. Many efficient approaches exist to compute a solution quickly. However, we consider whether the nature of the data fitting in this formulation allows for reasonable assumptions to be made about the solution that can improve the computational performance further. In particular, we employ a well known dual formulation of this problem and solve the corresponding equations in a restricted domain. We present experimental results that explore the dependence of the solution on this restriction and quantify imrovements in the computational performance. This approach can be extended to analogous methods simply and could provide an efficient alternative for problems of this type.