Given M sampled image values of an incoherent object, what can be deduced as the most
likely object? Using a communication-theory model for the process of image formation, we …

Many linear image restoration methods minimize a compound criterion which balances
some fidelity to the observed data via a least-squares measure, and some fidelity to prior …

We present a new algorithm for image restoration in limited-angle chromotomography. The
algorithm is a generalization of the technique considered previously by the authors, based …

A regularized algorithm for the recovery of band-limited signals from noisy data is described.
The regularization is characterized by a single parameter. Iterative and non-iterative …

Regularization is an effective method for obtaining satisfactory solutions to image restoration
problems. The application of regularization necessitates a choice of the regularization …

Linear, nonlinear, and iterative image-reconstruction (IR) algorithms are reviewed.
Theoretical results are presented concerning controllable linear filters, the solution of ill …

Bajkova's generalized maximum entropy method for reconstruction of complex signals is
further generalized through the use of Kullback–Leibler cross entropy. This permits a priori …

This paper studies the recovery of a superposition of point sources from noisy bandlimited
data. In the fewest possible words, we only have information about the spectrum of an object …

Publisher Summary Image recovery is a broad discipline that encompasses the large body
of inverse problems, in which an image h is to be inferred from the observation of data x …

Linear and nonlinear image restoration methods have been studied in depth but have
always been treated separately. In this paper several well-known linear and nonlinear …