Pre-processing of hyperspectral images. Essential steps before image analysis

Hyperspectral Imaging is an essential technique to deep explore surfaces in which more detail than the one provided by the single point spectroscopy is needed. Many devices for acquiring hyperspectral images have been manufactured and there is an increasing interest for improving the data analysis techniques applied to such complex datasets. Regardless the instrumentation, the acquisition of the images is being constantly improved by setting faster and more robust detectors, including new cooling systems or improving the light sources. Nevertheless, there are several issues that must be handled before starting the data analysis of any sample (e.g. background removal, compression of the images, spiked points, dead pixels, etc.). Therefore, the step of image pre-processing is almost always required. The aim of this paper is to show the application of some of the most common possibilities to solve the above mentioned issues before the image processing. This is done in a practical way, providing examples of their application, pros and cons as well as their implementation. For this purpose, several real examples (pharmaceutical tablets and food stuff) have been used throughout this manuscript (C) 2012 Elsevier B.V. All rights reserved.