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Multi-spectral image |
Multi-spectral imaging is a technology originally developed for space-based imaging. Multi-spectral imaging can capture light from frequencies beyond the visible light range, such as infrared. This can allow extraction of additional information that the human eye fails to capture with its receptors for red, green and blue.
Multi-spectral images are the main type of images acquired by Remote sensing (RS) radiometers. Multi-spectral is the opposite of panchromatic. Usually satellites have 3 to 7 or more radiometers (Landsat has 7). Each one acquires one digital image (in remote sensing, called a scene) in a small band of visible spectra, ranging 0.7 µm to 0.4 µm, called red-green-blue (RGB) region, and going to infra-red wavelengths of 0.7 µm to 10 or more µm, classified as NIR-Near InfraRed, MIR-Middle InfraRed and FIR-Far InfraRed or Thermal. In the Landsat case there are 7 scenes comprising a 7 band multi spectral image.
This technology has also assisted in the interpretation of ancient papyri such as those found at Herculaneum, by imaging the fragments in the infrared range (1000nm). Often the text on the documents appears to be as black ink on black paper to the naked eye. At 1000nm, the difference in light reflectivity makes the text clearly readable. It has also been used to image the Archimedes Palimpsest by imaging the parchment leaves in bandwidths from 365-870 nm and then using advanced digital image processing techniques to reveal the under text of Archimedes work.
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The wavelengths are approximate; exact values depend on the particular satellite's instruments:
For different purposes, different combinations of spectral bands can be used. They are usually represented with red, green, and blue channels. Mapping of bands to colors depends on the purpose of the image and the personal preferences of the analysts. Thermal infrared is often omitted from consideration due to poor spatial resolution, except for special purposes.
Many other combinations are in use. Near infrared is often shown as red, making vegetation covered areas appear red.