High‐order variational models are powerful methods for image processing and analysis, but
they can lead to complicated high‐order nonlinear partial differential equations that are …

Euler's elastica model has a wide range of applications in image processing and computer
vision. However, the nonconvexity, the nonsmoothness, and the nonlinearity of the …

The curvature regularities are well-known for providing strong priors in the continuity of
edges, which have been applied to a wide range of applications in image processing and …

This paper proposes two numerical algorithms for solving Euler's elastica-based inpainting
model. The minimizing functional is nonsmooth and nonconvex and involves high-order …

The curvature regularities have received growing attention with the advantage of providing
strong priors in the continuity of edges in image processing applications. However, owing to …

The multi-channel total variation (MTV) based on L2 norm is capable of preserving object
edges and smoothing flat regions in color images. However, it will lead to loss of image …

For curves or general interfaces, Euler's elastica energy has a wide range of applications in
computer vision and image processing. It is however difficult to minimize the functionals …

Image segmentation with depth information can be modeled as a minimization problem with
Nitzberg–Mumford–Shiota functional, which can be transformed into a tractable variational …

Segmentation has been widely studied and is one of the fundamental and classical tasks of
image processing. Starting from Mumford–Shah functional, we review multiphase …

The Euler's elastica energy regularizer has been widely used in image processing and
computer vision tasks. However, finding a fast and simple solver for the term remains …