In the age of artificial intelligence, the best approach to handling huge amounts of data is a
tremendously motivating and hard problem. Among machine learning models, stochastic …

We propose a new plug-and-play image restoration method based on primal-dual splitting.
Existing plug-and-play image restoration methods interpret any off-the-shelf Gaussian …

We propose a new definition for the gradient field of a discrete image defined on a twice
finer grid. The differentiation process from an image to its gradient field is viewed as the …

We study TV regularization, a widely used technique for eliciting structured sparsity. In
particular, we propose efficient algorithms for computing prox-operators for lp-norm TV. The …

In this work we propose a new splitting technique, namely Asymmetric Forward–Backward–
Adjoint splitting, for solving monotone inclusions involving three terms, a maximally …

Proximal splitting algorithms are well suited to solving large-scale nonsmooth optimization
problems, in particular those arising in machine learning. We propose a new primal-dual …

Background Optimization of the dose the patient receives during scanning is an important
problem in modern medical X-ray computed tomography (CT). One of the basic ways to its …

Dynamic range limitations in signal processing often lead to clipping, or saturation, in
signals. The task of audio declipping is estimating the original audio signal, given its clipped …

Speckle noise is a major problem in medical ultrasound imaging that reduces the image
quality and leads to a negative impact on further diagnosis. In this paper, aiming to alleviate …

超分辨率重建是当前卫星遥感数据空间分辨率提升的重要技术, 但目前现有的超分辨率重建方法
在处理具有复杂地物特征的影像时效果往往不佳. 当遥感影像中包含有各种非均匀地物信息时 …