Advances in Imaging and Electron Physics, Volume 124

Four of the six contributions to this volume are concerned with aspects of signal filtering, which of course includes image filtering for noise suppression and quality improvement. The first, by A. Carini. E. Mumolo and G. L. Sicuranza, is concerned with the class of polynomial filters known as Volterra filters.

Sampling theory is a vast subject with a long history, in which the Whittaker-Shannon-Kotel’nikov formula is the best known event. A. G. García surveys the various approaches to sampling and explains the results that have been obtained over the years.

The third chapter brings us back to filtering—here it is kriging that is examined. W. S. Kerwin and J. L. Prince show that, with suitable assumptions, space-time kriging (and the related cokriging) can be performed by means of fast filtering techniques.

In his discussion of orthogonal and biorthogonal scaling functions and multiwavelets constructed with the aid of fractal interpolation surfaces, B. Kessler gives an account of the most recent results in an area in rapid development.

Although the most familiar technique tor obtaining three-dimensional information about the human body is tomography using x-rays, this is not the only wavelength range that can be used. Optical diffusion tomography, in which light is used instead of x-rays, is attractive in that the radiation is not ionizing and the equipment is much less expensive; furthermore, the image may give functional information about the tissues and organs irradiated. The major drawback is that light is scattered in its passage through the body and image interpretation is much less direct. This is the subject of the chapter by C. L. Matson, on diffraction tomography in turbid media.

The final chapter brings us back to filtering, the objective here being noise reduction in images based on wavelet decomposition. J. S. Walker presents the technique pioneered by him that is known as tree-adapted wavelet shrinkage (TAWS).