Sobolev gradients for segmentation of vector-valued texture images
作者：
Highlights：
• To propose a variational model to smooth, segment vector-valued texture images. The model is extension of the model (M2).
• We first smooth texture in image F0 through L0 norm in to get smooth image I, and then segmentation model is implemented.
• A dual minimization technique is applied i.e., Sobolev gradient for minimization of length and L2 norm for fidelity term.
• Semi-Implicit (SI) method is used for the solution of the Partial Differential Equation arisen from the proposed model.
• Numerical results of the proposed model are compared with state-of-the-art L2 gradients.
摘要
•To propose a variational model to smooth, segment vector-valued texture images. The model is extension of the model (M2).•We first smooth texture in image F0 through L0 norm in to get smooth image I, and then segmentation model is implemented.•A dual minimization technique is applied i.e., Sobolev gradient for minimization of length and L2 norm for fidelity term.•Semi-Implicit (SI) method is used for the solution of the Partial Differential Equation arisen from the proposed model.•Numerical results of the proposed model are compared with state-of-the-art L2 gradients.
论文关键词：Vector-valued texture images,L0 norm,L2 norm,Sobolev gradients,Level sets,Partial differential equations,Semi-implicit method
论文评审过程：Received 9 August 2019, Revised 12 December 2020, Accepted 3 January 2021, Available online 10 March 2021, Version of Record 10 March 2021.
论文官网地址：https://doi.org/10.1016/j.amc.2021.125962
