In this paper, we analyze the convergence of the alternating direction method of multipliers
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …

Rigid registration of two geometric data sets is essential in many applications, including
robot navigation, surface reconstruction, and shape matching. Most commonly, variants of …

Group sparse representation (GSR) has made great strides in image restoration producing
superior performance, realized through employing a powerful mechanism to integrate the …

In this paper, we propose a fast optimisation algorithm for approximately minimising convex
quadratic functions over the intersection of affine and separable constraints (ie the Cartesian …

Convex optimization with sparsity-promoting convex regularization is a standard approach
for estimating sparse signals in noise. In order to promote sparsity more strongly than …

Abstract The ${{\ell}}^{0} $ minimization of compressed sensing is often relaxed to
${{\ell}}^{1} $, which yields easy computation using the shrinkage mapping known as soft …

Sparse coding has achieved a great success in various image processing tasks. However, a
benchmark to measure the sparsity of image patch/group is missing since sparse coding is …

This paper deals with the problem of reconstructing a depth map from a sequence of
differently focused images, also known as depth from focus (DFF) or shape from focus. We …

The deployment of smart grids and renewable energy dispatch centers motivates the
development of forecasting techniques that take advantage of near real‐time measurements …

Hyperspectral sparse unmixing aims at finding the optimal subset of spectral signatures in
the given spectral library and estimating their proportions in each pixel. Recently …