Explanation:

Whereas the human eye sees colour of visible light in mostly three bands (red, green, and blue), spectral imaging divides the spectrum into many more bands.

This technique of dividing images into bands can be extended beyond the visible.

In hyperspectral imaging, the recorded spectra have fine wavelength resolution and cover a wide range of wavelengths. This can cover very fine imaging.

Justification: Statement 1: Known as spectral signatures, these 'fingerprints' enable identification of the materials that make up a scanned object. For example, a spectral signature for oil helps geologists find new oil fields.

Statement 2: Although the cost of acquiring hyperspectral images is typically high, for specific crops and in specific climates, hyperspectral remote sensing use is increasing for monitoring the development and health of crops. This is because the finer colours that indicate crop health can be mapped by hyperspectral imaging.

Statement 3: Researchers in Montraal are working to test the use of hyperspectral photography in the diagnosis of retinopathy and macular edema before damage to the eye occurs.

Statement 4: In the food processing industry, hyperspectral imaging, combined with intelligent software, enables digital sorters (also called optical sorters) to identify and remove defects and foreign material (FM) that are invisible to traditional camera and laser sorters.