What is hyperspectral imaging?
Hyperspectral imaging is a non-destructive, non-contact technology which makes it ideal for a wide range of applications. In recent years, hyperspectral imaging technique has been regarded as a smart analytical tool for analyses conducted in research, control, and industries. The goal of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials, or detecting processes.

How does it work?

A hyperspectral imaging system produces a two dimensional spatial array of vectors which represents the spectrum at each pixel location. The resulting three-dimensional dataset containing the two spatial dimensions and one spectral dimension is known as the datacube or hypercube.

Advantages and disadvantages of hyperspectral imaging?

The advantages of hyperspectral imaging over the traditional methods include minimal sample preparation, nondestructive nature, fast acquisition times, and visualizing spatial distribution of numerous chemical compositions simultaneously.

The primary disadvantages are cost and complexity. Fast computers, sensitive detectors, and large data storage capacities are needed for analyzing hyperspectral data. Significant data storage capacity is necessary since hyperspectral cubes are large, multidimensional datasets, potentially exceeding hundreds of megabytes. All of these factors greatly increase the cost of acquiring and processing hyperspectral data.