Light is absorbed and scattered when it travels though water, which causes the captured
underwater images often suffering from blurring, low contrast and color degradation. To …

In this work, we investigate image registration in a variational framework and focus on
regularization generality and solver efficiency. We first propose a variational model …

Underwater images often suffer from various degradations such as blurring, fog, low
contrast, and color distortion because the light is absorbed and scattered when traveling …

Magnetic resonance imaging (MRI) reconstruction is an active inverse problem which can
be addressed by conventional compressed sensing (CS) MRI algorithms that exploit the …

Total variation (TV) is a powerful regularization method that has been widely applied in
different imaging applications, but is difficult to apply to diffuse optical tomography (DOT) …

A number of variational models for image denoising have been proposed in the last few
years in order to improve the denoising performance of the classical Rudin-Osher-Fatemi …

In order to remove speckle noise while preserving image features, a novel variational model
for image restoration based on total curvature is proposed in this paper. Due to the …

Speckle noise removal problem has been researched under the framework of regularization-
based approaches. The regularizer is normally defined as total variation (TV) that induces …

Compressed sensing magnetic resonance imaging (CS-MRI) has attracted considerable
attention due to its great potential in reducing scanning time and guaranteeing high-quality …

Characteristics of an image, such as smoothness, edge, and texture, can be better
preserved using the nonlocal differential operator in image processing. We establish an L 1 …