This paper presents a new approach to image deconvolution (deblurring), under total
variation (TV) regularization, which is adaptive in the sense that it does not require the user …

Abstract This Technical Design Report presents a detailed description of all aspects of the
LUXE (Laser Und XFEL Experiment), an experiment that will combine the high-quality and …

We consider the problem of optimizing the parameters of a given denoising algorithm for
restoration of a signal corrupted by white Gaussian noise. To achieve this, we propose to …

This paper answers the challenge as how to automatically select a good regularization
parameter when solving inverse problems in acoustics. A Bayesian solution is proposed that …

A full‐Bayesian approach to the estimation of transmissivity from hydraulic head and
transmissivity measurements is developed for two‐dimensional steady state groundwater …

In this paper, we propose a novel deconvolution algorithm based on the minimization of a
regularized Stein's unbiased risk estimate (SURE), which is a good estimate of the mean …

Most modern imaging systems incorporate a computational pipeline to infer the image of
interest from acquired measurements. The Bayesian approach to solve such ill-posed …

The L-curve is a popular heuristic to tune Tikhonov regularization in linear inverse problems.
This paper shows how it naturally arises when the problem is solved from a Bayesian …

We propose an alternate minimization algorithm for estimating the point-spread function
(PSF) of a confocal laser scanning microscope and the specimen fluorescence distribution …

In this article, we propose a novel blind image deconvolution method developed within the
Bayesian framework. We concentrate on the restoration of blurred photographs taken by …