Developments in the theory of image reconstruction and restoration over the past 20 or 30
years are outlined. Particular attention is paid to common estimation structures and to …

It is learned from elementary textbooks that the angular resolution of a perfect optical
telescope is limited by diffraction to an angle in radians of about A ID, the ratio of the …

Let T be a (possibly nonlinear) continuous operator on Hilbert space. If, for some starting
vector x, the orbit sequence {T kx, k= 0, 1,...} converges, then the limit z is a fixed point of T; …

Much has been written on the theory and applications of iterative algorithms, so any book on
the subject must be but a glimpse. The topics included here are those most familiar to me …

In many applications of computed tomography, it may not be possible to acquire projection
data at all angles, as required by the most commonly used algorithm of convolution …

This book explains how mathematical tools can be used to solve problems in signal
processing. Assuming an advanced undergraduate-or graduate-level understanding of …

An algorithm is developed to define, from the data samples themselves, a frequency-
weighted norm to use in minimum-weighted-norm extrapolation. The iterative procedure …

Iterative Optimization in Inverse Problems brings together a number of important iterative
algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent …

" This beautiful book can be read as a novel presenting carefully our quest to get more and
more information from our observations and measurements. Its authors are particularly good …

Two methods of matrix inversion are compared for use in an image reconstruction algorithm.
The first is based on energy minimization using a Hopfield neural network. This is compared …