multispectral

Multispectral imaging is the capture and analysis of image data in a limited number of spectral bands, typically three to ten, that extend beyond the standard red–green–blue channels. Each band corresponds to a specific wavelength interval, commonly including visible and near-infrared regions and sometimes short-wave infrared. The approach provides information about material properties through spectral reflectance or emissivity.

Technologies for multispectral imaging include cameras with fixed filters, rotating filter wheels, or snapshot sensors that acquire multiple bands simultaneously. Common bands cover blue, green, red, and near-infrared, with some systems adding red edge or short-wave infrared channels. Sensor platforms range from modified consumer cameras to airborne and satellite instruments, as well as industrial imaging systems used in quality control.

Applications span remote sensing, land and water resource management, agriculture, forestry, and environmental monitoring, with agricultural use often leveraging vegetation indices to assess plant health. Multispectral imaging is also employed in medical research, forensics, archaeology, and industrial inspection, where spectral information helps distinguish materials or detect defects.

Compared with hyperspectral imaging, multispectral captures fewer and broader spectral bands, producing smaller data volumes, simpler hardware, and faster acquisition and processing. This comes at the cost of reduced spectral resolution and material-identification precision. Data processing typically involves radiometric calibration, geometric correction, and, for airborne or satellite data, atmospheric correction. Analysts may use band math, vegetation indices, and classification techniques. Multispectral data can be enhanced by combining with higher-resolution panchromatic imagery in pansharpening to improve spatial detail.