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科学研究
报告题目:

Multi-Phase Image Segmentation by the Allen--Cahn Chan--Vese Model

报告人:

乔中华 教授(香港理工大学)

报告时间:

报告地点:

腾讯会议ID:426-933-166

报告摘要:

We propose an Allen--Cahn Chan--Vese model to settle the multi-phase image segmentation. We first integrate the Allen--Cahn term and the Chan--Vese fitting energy term to establish an energy functional, whose minimum locates the segmentation contour. The subsequent minimization process can be attributed to variational calculation on fitting intensities and the solution approximation of several Allen--Cahn equations, wherein n Allen--Cahn equations are enough to partition m = 2n segments. The derived Allen--Cahn equations are solved by efficient numerical solvers with exponential time integrations and finite difference space discretization. The discrete maximum bound principle and energy stability of the proposed numerical schemes are proved. Finally, the capability of our segmentation method is verified in various experiments for different types of images.

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