In this paper, we propose a fast and efficient way to restore blurred and noisy images with a
high-order total variation minimization technique. The proposed method is based on an …

In this paper, we use the cosine function to express the data energy fitting of a traditional
active contours model and propose a model based on sectional image recovery local cosine …

Restoration of images degraded by blurring and impulse noise has received considerable
attention recently. Guo et al.(2009) proposed a fast l 1-total variation algorithm for grayscale …

Reflexive boundary conditions (BCs) assume that the array values outside the viewable
region are given by a symmetry of the array values inside. The reflection guarantees the …

In this paper, we consider an ill-posed image restoration problem with a noise contaminated
observation, and a known convolution kernel. A special Hermitian and skew-Hermitian …

In this paper, a Bregman iteration based total variation image restoration algorithm is
proposed. Based on the Bregman iteration, the algorithm splits the original total variation …

Image decomposition denotes a process by which an image is decomposed into several
different scales, such as cartoon, texture (or noise) and edge. In order to better separate the …

The augmented Lagrangian strategy has recently emerged as an important methodology for
image processing problems. In this paper, based on this strategy, we propose a new …

Variational decomposition has been widely used in image denoising, however, it can't
distinguish texture from noise well. Replacing the fixed parameter in the (BV, G) …

We consider simultaneously estimating the restored image and the spatially dependent
regularization parameter which mutually benefit from each other. Based on this idea, we …