To improve the image segmentation quality, it is important to adequately describe the local
features of targets in images. In this paper, we develop a novel adaptive total variation …

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 …

Gaussian curvature is an important geometric property of surfaces, which has been used
broadly in mathematical modeling. Due to the full nonlinearity of the Gaussian curvature …

Image segmentation is a significant problem in image processing. In this paper, we propose
a new two-stage scheme for segmentation based on the Fischer-Burmeister total variation …

Solving variational image segmentation problems with hidden physics is often expensive
and requires different algorithms and manually tuned model parameters. The deep learning …

Natural images are usually composed of multiple objects at different scales in flat and
slanted regions. Traditional labeling/segmentation approaches based on total variation …

Image segmentation is a fundamental and challenging task in image processing and
computer vision. The colour image segmentation is attracting more attention as the colour …

This paper presents a numerical scheme to address a type of fractional spatial–temporal
telegraph equations with variable coefficients by applying the modified fractional Legendre …

In this paper, a novel active contour model based on hybrid image fitting energy which
utilizes both global and local image information is proposed. Two fitting images are …

Image deblurring model with computationally expensive regularization is used to improve
the quality of the deblurred images. These models are very efficient in preserving edges and …