An Efficient Local Radial Basis Function Method for Image Segmentation Based on the Chan–Vese Model
Shupeng Qiu,
Chujin Lin,
Wei Zhao
Abstract:In this paper, we consider the Chan-Vese (C-V) model for image segmentation and obtain its numerical solution accurately and efficiently. For this purpose, we present a local radial basis function method based on a Gaussian kernel (GA-LRBF) for spatial discretization. Compared to the standard radial basis function method, this approach consumes less CPU time and maintains good stability because it uses only a small subset of points in the whole computational domain. Additionally, since the Gaussian function ha… Show more
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