Hyperspectral Image Processing Techniques

Hyperspectral imaging is the combination of two mature technologies:spectroscopy and imaging. In this technology, an image is acquired over thevisible and near-infrared (or infrared) wavelengths to specify the completewavelength spectrum of a sample at each point in the imaging plane.Hyperspectral images are composed of spectral pixels, corresponding toa spectral signature (or spectrum) of the corresponding spatial region. Aspectral pixel is a pixel that records the entire measured spectrum of theimaged spatial point. Here, the measured spectrum is characteristic ofa sample’s ability to absorb or scatter the exciting light.The big advantage of hyperspectral imaging is the ability to characterizethe inherent chemical properties of a sample. This is achieved by measuringthe spectral response of the sample, i.e., the spectral pixels collected from thesample. Usually, a hyperspectral image contains thousands of spectral pixels.The image files generated are large and multidimensional, which makesvisual interpretation difficult at best. Many digital image processing tech-niques are capable of analyzing multidimensional images. Generally, theseare adequate and relevant for hyperspectral image processing. In somespecific applications, the design of image analysis algorithms is required forthe use of both spectral and image features. In this chapter, classic imageprocessing techniques and methods, many of which have been widely usedinhyperspectral imaging, will be discussed, as well as some basic algorithmsthat are special for hyperspectral image analysis.