The ill-posed problem of restoring object information from finitely many measurements of its
spectrum can be solved by using the best approximation in Hilbert spaces appropriately …

In reconstructing an object function F (r) from finitely many noisy linear-functional values∫ F
(r) G_n (r) dr we face the problem that finite data, noisy or not, are insufficient to specify F (r) …

An analysis is carried out, using the prolate spheroidal wave functions, of certain regularized
iterative and noniterative methods previously proposed for the achievement of object …

The two entropy expressions, log B and− B logB (where B is the local brightness of the
object or its spatial spectral power) used in maximum entropy (ME) image restoration, are …

A new strategy for signal and image reconstruction with incomplete information and partial
constraints is defined. The main purpose of the first paper (part I) is to specify the conditions …

As band-limited interpolation is possible to some extent, whereas band-limited extrapolation
is strictly forbidden, it is natural to state the deconvolution problem in terms of weighted …

The method of projections onto convex sets can be used to solve many problems in image
restoration, eg, restoration from phase, spectral extrapolation, and signal recovery in …

Maximum entropy (ME) inversion is a non‐linear inversion technique for inverse problems
where the object to be recovered is known to be positive. It has been applied in areas …

The problem of reconstructing a non-negative function from finitely many values of its Fourier
transform is a problem of approximating one function by another and, as such, is analogous …

Stable, noniterative object reconstruction from incomplete data using a priori knowledge
clickable element to expand a topic LOGIN OR CREATE ACCOUNT PRISM SUBMISSION This …