M. Wolkenstein

Visualization of n-dimensional analytical data on personal computers

Abstract Visualization is the task of creating images that allow important features in the data to be discerned much more readily than from the raw data. In this article we describe our efforts towards using three-dimensional graphics for improved visualization of different data from analytical chemistry. Various available algorithms are used to analyze and visualize data features that are otherwise difficult to grasp. A selection of case studies is presented to demonstrate the capabilities of data visualization. It is shown that, despite some limitations in computing power, it is perfectly feasible to use standard personal computers for advanced data visualization tasks.

Chapter 20 – Wavelet Analysis and Processing of 2-D and 3-D Analytical Images

This chapter describes several applications of wavelet methods to analyze and process analytical images. A short list of online resources on wavelets and wavelet analysis with focus on their application to analytical images is discussed. The chapter enlists some recent results considering the application of wavelet analysis and processing to 2-D and 3-D analytical images. It introduces the theory of the 2-D and 3-D separable discrete wavelet transform. Several applications of algorithms based on the wavelet transform are described: (1) wavelet de-noising of 2-D and 3-D SIMS images; (2) improvement of analytical image classification by means of wavelet de-noising; (3) compression of 2-D and 3-D analytical images; (4) feature extraction from analytical images, that is, edge detection and texture analysis in the wavelet domain; (5) registration of images obtained by complementary techniques (EPMA and SIMS), based on their wavelet transform maxima (multiscale edges); and (6) wavelet fusion of multispectral SIMS images.