A multispectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, i.e. infrared and ultra-violet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its receptors for red, green and blue. It was originally developed for space-based imaging, and has also found use in document and painting analysis.
Multispectral imaging measures light in a small number (typically 3 to 15) number of spectral bands. Hyperspectral imaging is a special case of spectral imaging where often hundreds of contiguous spectral bands are available.
Most radiometers for remote sensing (RS) acquire multispectral images. Dividing the spectrum into many bands, multispectral is the opposite of panchromatic, which records only the total intensity of radiation falling on each pixel. Usually, Earth observation satellites have three or more radiometers (Landsat has seven). Each acquires one digital image (in remote sensing, called a 'scene') in a small spectral band. The bands are grouped into wavelength regions based on the origin of the light. The shortest wavelength region is the ultra-violett (wavelengths < 0.4 µm), followed by the visible, or VIS, region, ranging from 0.4 µm to 0.7 µm. The others are the near-infrared with wavelengths from 0.7 µm to 1 µm, followed by the Short-Wave-Infrared (SWIR) from 1 µm to 2.5 µm, the middle infrared (MIR) from 4 µm to 6 µm, and far, or thermal infrared (FIR or thermal) from 8 µm to 14 µm. In the Landsat case, the seven scenes comprise a seven-band multispectral image. Spectral imaging with more numerous bands, finer spectral resolution or wider spectral coverage may be called hyperspectral or ultraspectral.