![]() ![]() Of particular interest is an IMS system that demonstrates high spatial sampling of 355 × 350 over 41 wavelengths, using a single large format CCD image sensor. These features enable applications that require the ability to distinguish objects with similar spectral properties at high temporal resolution. ![]() 16– 18 By collecting information simultaneously, while utilizing simple datacube remapping algorithms, these systems add several powerful capabilities to HSI, including faster data collection and image reconstruction, higher light-throughput, less motion artifacts, and real-time spectral unmixing. There are three major modalities in this group: image slicers, 13 field splitting by fibers 14 or lenslet arrays, 15 and image mapping spectrometers (IMS). A transformation is then used to reconstruct the 3-D hyperspectral datacube from the 2-D image recorded on an image sensor.Īnother class of snapshot HSI systems provides all spatial-spectral information on a single or multiple CCD image sensors with a one-to-one correspondence between datacube voxels and detector pixels. 10– 12 These “snapshot” instruments incorporate specialized components to distribute an object's 3-D spatial-spectral information onto a two-dimensional (2-D) focal plane array. Some examples of such systems are the computed tomographic imaging spectrometer (CTIS) and the coded aperture snapshot spectral imager (CASSI). More recently, a class of hyperspectral imagers has come forward that collects the entire datacube simultaneously. 6 These systems include pushbroom, whiskbroom, liquid-crystal tunable filter (LCTF), acousto-optic tunable filter (AOTF), digital micromirror device (DMD), 7 and Fourier transform 8, 9 based imaging spectrometers. 5 Traditional hyperspectral imagers implement a temporal scanning technique to sequentially collect the hyperspectral datacube by either point-scanning, line-scanning, wavelength-scanning, or compressive sampling. Linear unmixing or other spectral analysis algorithms can use this spatial-spectral dataset in order to identify concentrations of chemicals within a scene. 4 By collecting both spatial and spectral information about an object, it provides a full three-dimensional (3-D) distribution, called a hyperspectral datacube. Hyperspectral imaging (HSI) is utilized throughout the fields of astronomy, 1 remote sensing, 2 food science, 3 and biotechnology. ![]()
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