Two-phase segmentation for intensity inhomogeneous images by the Allen-Cahn Local Binary Fitting Model
From MaRDI portal
Publication:6378373
DOI10.1137/21M1421830arXiv2109.11262MaRDI QIDQ6378373
Qian Zhang, Zhonghua Qiao, Chaoyu Liu
Publication date: 23 September 2021
Abstract: This paper proposes a new variational model by integrating the Allen-Cahn term with a local binary fitting energy term for segmenting images with intensity inhomogeneity and noise. An inhomogeneous graph Laplacian initialization method (IGLIM) is developed to give the initial contour for two-phase image segmentation problems. To solve the Allen-Cahn equation derived from the variational model, we adopt the exponential time differencing (ETD) method for temporal discretization, and the central finite difference method for spatial discretization. The energy stability of proposed numerical schemes can be proved. Experiments on various images demonstrate the necessity and superiority of proper initialization and verify the capability of our model for two-phase segmentation of images with intensity inhomogeneity and noise.
Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Stability and convergence of numerical methods for initial value and initial-boundary value problems involving PDEs (65M12) Numerical solution of discretized equations for initial value and initial-boundary value problems involving PDEs (65M22)
This page was built for publication: Two-phase segmentation for intensity inhomogeneous images by the Allen-Cahn Local Binary Fitting Model
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6378373)
