Two-step version of fixed point continuation method for sparse reconstruction

l₁-regularized problems have a wide application in various areas such as signal processing. It minimizes a quadratic function combined with an l₁ norm term. Iterative soft-thresholding method (IST) is originally proposed to deal with these problems, and fixed point continuation algorithm (FPC) was proposed recently as an improved version of IST. This paper obtains a two-step version of FPC (TwFPC) by combining the new iterate of FPC with its previous two iterates. We also provide an analysis for the convergence of FPC and TwFPC. Various numerical experiments on image deconvolution and compressed sensing show that TwFPC improves IST significantly and is much faster than other competing codes. What is more important, it is very robust to the involved parameters and the regularization parameter.