What is Hyperspectral Imaging?
Hyperspectral imaging or spectral imaging, collects and processes information from across the electromagnetic spectrum. The human eye sees visible light in three bands (red, green, and blue), with spectral imaging it is possible to look into many more bands. This technique enables its user to identify spectral features that are not visible for common cameras or the human eye. Those features usually are directly related to the optical properties of the analysed materials.
Due to the fact that each material has a different spectral signature such data has the potential not only to separate specific materials from others, but also allowing it to make qualitative statements on the analysed object.
Hyperspectral sensors look at objects using a vast portion of the electromagnetic spectrum. Certain objects leave unique ‚fingerprints‘ across the electromagnetic spectrum. These ‚fingerprints‘ are known as spectral signatures and enable identification of the materials that make up a scanned object.
Hyperspectral data cube
Hyperspectral cubes are generated by hyperspectral imaging sensors. Hyperspectral sensors collect information as a set of ‚images‘. Each image represents a range of the electromagnetic spectrum and is also known as a spectral band. These ‚images‘ are then combined and form a three-dimensional hyperspectral data cube for processing and analysis.
Multispectral vs. Hyperspectral
Depending on the number of spectral bands and wavelengths measured, an image is classified as a multispectral image when only a small number of bands are measured and these bands usually are relatively broad. An image is classified as hyperspectral when a complete wavelength region, i.e., the whole spectrum, is measured for each spatial point. For example, an RGB image from a typical digital camera is a type of multispectral image that uses the light intensity at three specific wavelengths: red, green, and blue, to create an image in the visible region.