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Multispectral imaging captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or detected with the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range (i.e. infrared and ultraviolet ).
Subcategories of multispectral remote sensing include hyperspectral, in which hundreds of bands are collected and analyzed, and ultraspectral remote sensing where many hundreds of bands are used (Logicon, 1997). The main purpose of multispectral imaging is the potential to classify the image using multispectral classification.
Two-dimensional projection of a hyperspectral cube. Hyperspectral imaging collects and processes information from across the electromagnetic spectrum. [1] The goal of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials, or detecting processes.
Hyperspectral images are often represented as an image cube, which is type of data cube. [3] Applications of spectral imaging [4] include art conservation, astronomy, solar physics, planetology, and Earth remote sensing. It also applies to digital and print reproduction, and exhibition lighting design for small and medium cultural institutions. [5]
Spectroradiometry is a technique in Earth and planetary remote sensing, which makes use of light behaviour, specifically how light energy is reflected, emitted, and scattered by substances, to explore their properties in the electromagnetic (light) spectrum and identify or differentiate between them. [1]
Remote sensing can be divided into two types of methods: Passive remote sensing and Active remote sensing. Passive sensors gather radiation that is emitted or reflected by the object or surrounding areas. Reflected sunlight is the most common source of radiation measured by passive sensors.
The Remote Sensing Center works with airborne and satellite systems including IKONOS/Quickbird multispectral imagery (MSI), and airborne hyperspectral imaging (HSI) systems including AVIRIS, HYDICE, CASI, and HYMAP. Classification and analysis, including atmospheric compensation is performed using standard industry research tools; notably ENVI ...
Hyperspectral data is often used to determine what materials are present in a scene. Materials of interest could include roadways, vegetation, and specific targets (i.e. pollutants, hazardous materials, etc.). Trivially, each pixel of a hyperspectral image could be compared to a material database to determine the type of material making up the ...
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