This paper presents a new algorithm for image denoising using a fractional integral mask of
the K-operator. K-operator is the generalized fractional operator, and it reduces to Riemann …

Infrared (IR) images are often contaminated by obvious intensity bias and stripes, which
severely affect the visual quality and subsequent applications. It is challenging to eliminate …

Removing specular reflections from images is critical for improving the performance of
computer vision algorithms. Recently, state-of-the-art methods have demonstrated …

In this paper, we address the image denoising problem in presence of speckle degradation
typically arising in ultra-sound images. Variational methods and Convolutional Neural …

We present a total-variation-regularized image segmentation model that uses local
regularization parameters to take into account spatial image information. We propose some …

Abstract Background and objective Bioluminescence Tomography (BLT) is a powerful
optical molecular imaging technique that enables the noninvasive investigation of dynamic …

Image reconstruction is important for activities that rely on optical and comparative data
analysis. Signals obtained through acquisition systems can be inconsistent due to several …

The Plug-and-Play framework has demonstrated that a denoiser can implicitly serve as the
image prior for model-based methods for solving various inverse problems such as image …

Accurately reconstructing functions with discontinuities is the key tool in many bio-imaging
applications as, for instance, in Magnetic Particle Imaging (MPI). In this paper, we apply a …

We propose a subspace-accelerated Bregman method for the linearly constrained
minimization of functions of the form $ f (\mathbf {u})+\tau_1\|\mathbf {u}\| _1+\tau_2 …