
Hyperspectral imaging is the process of collecting and processing of information across the electromagnetic spectrum. It is the combination of spectroscopy and digital imaging, implemented to create a spectral based contrast within the image. Hyperspectral images are formed with the help of an instrument called imaging spectrometer. These images are obtained at multiple wavelengths and shaped into a three-dimensional hyperspectral data cube with two spatial dimensions and one spectral dimension. Hyperspectral imaging also measures absorption of electromagnetic radiation, emission, and reflection; and provides a unique spectral signature for every pixel, used by processing techniques to identify and discriminate materials. Some of the advantages of hyperspectral imaging are the non-requirement of prior knowledge of the sample and the acquisition of entire spectrum at each point. In addition, it is an emerging imaging modality for the diagnosis of diseases and image guided surgeries. It provides extensive information for processing and analysis of the image. It also provides a continuous spectrum for each image cell and offers diagnostic information regarding tissue composition, morphology, and physiology. In addition, during the progression of the disease, the absorption, scattering, and fluorescence characteristics of the tissue change, and hyperspectral imaging helps in the diagnosis of the tissue pathology. It helps in diagnosis and treatment of diseases. It also helps improve the quality of life and reduces medical cost. It is also used in industries such as agriculture, mining, environmental monitoring, food, mining and mineralogy, military surveillance, life-science and medical diagnostics, and process vision. In the agriculture industry, hyperspectral imaging is used to monitor the development and health of crops.