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A new level set method with global alternating minimization algorithm for image segmentation
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AI
DOI：10.1016/j.apm.2025.116396.png)
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Abstract
En 中文
• The total variation term with edge information is introduced into convex energy, which improves ability to process weak edges and noise. • An efficient and fast alternating optimization algorithm is designed based on ADMM and FFT. • We eliminate the explicit dependence on the time step and ensure the flexibility of the solution on the time dimension. • The proposed model has a global minimum, showing superior segmentation on industrial CT data.
Keywords:
total variation
convex energy
ADMM
FFT
image segmentation
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