Advances in Imaging and Electron Physics, Volume 132

The six chapters that make up this latest volume of Advances in Imaging and Electron Physics cover evanescent waves, the relation between symmetry and the Karhunen-Loeve decomposition, electron microscopy of ceramics, a new formulation of relativistic quantum mechanics and multiscale transforms.

The chapter by H.F. Arnoldus on evanescent waves close to a source and their possible persistence in the far field explores the behaviour of these waves in great detail.

The second contribution, a study of symmetry and the Karhunen-Loeve decomposition by B. Lahme, is again very timely for the Karhunen-Loeve decomposition, or principal-component analysis, is extensively used.

Next, we have an analysis of irregularly sampled data by R. Piroddi and M. Petrou. Recent ideas on computer vision and image processing, particularly those inspired by the mechanism of the human visual system, suggest that tools for manipulating irregular samples directly would be advantageous and it is these that are described and analysed here.

From time to time, chapters have been included here on the microscopy of a particular type of specimen and the chapter by W.M. Rainforth on ceramics is a welcome example. He shows how much new information is being acquired by the various operating modes of modern electron microscopes: transmission and scanning transmission imaging; electron energy-loss spectroscopy, with a section on the use of a monochromator (of which only two commercial models were in operation at the time of writing); and energy-filtering transmission electron microscopy.

This is followed by an extremely original chapter by H. Rose, another regular contributor to these Advances, who shows that, contrary to widespread belief, the effect of spin on particle motion can be correctly incorporated into geometrical electron optics.

The volume concludes with further chapter in the area of signal and image analysis. J.-L. Starck, M. Elad and D. Donoho describe the use of redundant multiscale transforms for morphological component separation. The authors introduce the concepts of curvelets and ridgelets that have arisen from wavelet studies and show that they are useful in the quest for sparseness. The chapter concludes with practical examples of the technique.