The problem of multiplicative noise removal has attracted much attention in recent years.
Unlike additive noise, multiplicative noise destroys almost all information of an image; …

Nonlinear anisotropic diffusion has attracted a great deal of attention for its ability to
simultaneously remove noise and preserve semantic image features. This ability favors …

We consider the Euler's elastica-based model for an image noise removal problem. Several
recent works have demonstrated that Euler's elastica-based model performs better than the …

The Euler elastica (EE) model with surface curvature can generate artifact-free results
compared with the traditional total variation regularization model in image processing …

Recovering images corrupted by multiplicative noise is a well known challenging task.
Motivated by the success of multiscale hierarchical decomposition methods (MHDM) in …

In this paper, a convex variational model based on the adaptive total variation (TV)
regularization is proposed for image restoration under multiplicative noise. The adaptive …

A challenge in image restoration is to recover a clear image from the blurry observation in
the presence of different types of noise. There are few works addressing image deblurring …

Euler's elastica energy regularizer, initially employed in mathematical and physical systems,
has recently garnered much attention in image processing and computer vision tasks. Due …

This paper focuses on solving the multiplicative gamma denoising problem via a variation
model. Variation-based regularization models have been extensively employed in a variety …

In order to reconstruct accurate smooth implicit surfaces from skull point cloud data with
complex topological relations, a variational level set method based on Euler's Elastica …