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Hyperspectral imaging, like other spectral imaging, collects and processes information from across the electromagnetic spectrum. 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. The human eye sees color 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. Engineers build hyperspectral sensors and processing systems for applications in astronomy, agriculture, biomedical imaging, geosciences, physics, and surveillance. Hyperspectral sensors look at objects using a vast portion of the electromagnetic spectrum. Certain objects leave unique 'fingerprints' in the electromagnetic spectrum. 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.〔 〕 ==Hyperspectral image sensors== Figuratively speaking, hyperspectral sensors collect information as a set of 'images'. Each image represents a narrow wavelength range of the electromagnetic spectrum, also known as a spectral band. These 'images' are combined to form a three-dimensional (''x'',''y'',''λ'') hyperspectral data cube for processing and analysis, where ''x'' and ''y'' represent two spatial dimensions of the scene, and ''λ'' represents the spectral dimension (comprising a range of wavelengths).〔http://www.microscopyu.com/articles/confocal/spectralimaging.html〕 Technically speaking, there are four ways for sensors to sample the hyperspectral cube: Spatial scanning, spectral scanning, snapshot imaging,〔〔http://www.bodkindesign.com/wp-content/uploads/2012/09/Hyperspectral-1011.pdf〕 and spatio-spectral scanning.〔http://www.opticsinfobase.org/ao/abstract.cfm?uri=ao-53-20-4594〕 Hyperspectral cubes are generated from airborne sensors like the NASA's ''Airborne Visible/Infrared Imaging Spectrometer'' (AVIRIS), or from satellites like NASA's EO-1 with its hyperspectral instrument Hyperion.〔Schurmer, J.H., (Dec 2003), Air Force Research Laboratories Technology Horizons〕 However, for many development and validation studies, handheld sensors are used.〔Ellis, J., (Jan 2001) ''(Searching for oil seeps and oil-impacted soil with hyperspectral imagery ),'' Earth Observation Magazine.〕 The precision of these sensors is typically measured in spectral resolution, which is the width of each band of the spectrum that is captured. If the scanner detects a large number of fairly narrow frequency bands, it is possible to identify objects even if they are only captured in a handful of pixels. However, spatial resolution is a factor in addition to spectral resolution. If the pixels are too large, then multiple objects are captured in the same pixel and become difficult to identify. If the pixels are too small, then the energy captured by each sensor cell is low, and the decreased signal-to-noise ratio reduces the reliability of measured features. The acquisition and processing of hyperspectral images is also referred to as imaging spectroscopy or, with reference to the hyperspectral cube, as 3D spectroscopy. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「hyperspectral imaging」の詳細全文を読む スポンサード リンク
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