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Spectral Imaging

SSSC’s origins are based in spectral imaging, and SSSC maintains a particular expertise in this discipline.

SSSC specializes in spectral imaging in the EO/IR bands, including:
  • Visible (VIS) and Near Infrared (NIR) Imaging, from 400 nm to 1 µm
  • Short Wave Infrared (SWIR), from 1 – 3 µm
  • Medium Wave Infrared (MWIR), from 3 – 5.5 µm
  • Long Wave Infrared (LWIR), from 8 – 13 µm
Each EO/IR band may be divided into a multispectral (2 – 20) or hyperspectral (20 – 100) narrow color bands, depending on the application.

SSSC uses spectral imaging to exploit absorption bands, reflection bands, thermal emission bands, atmospheric transmission bands, and transition edges in order to realize a tactical or strategic advantage, such as:
  • Detect particular constituents
  • Discriminate material types
  • Mitigate background clutter
  • Identify targets
  • Reduce false alarm rates
  • See through cloud cover

Spectal Imaging Examples

VIS/NIR: Camouflage Detection
Exploiting phenomenological differences between how light reacts (reflects, transmits, or absorbs) with natural foliage and artificial materials is one application of spectral imaging.  For example, foliage reflects light in the visible green band, but absorbs in the NIR and SWIR; nylon netting and painted metal behave differently.

The video below shows imagery from, left to right, a commercial RGB camera,  SSSC 's 16-color VIS/NIR binned into RGB,  and SSSC 's 16-color VIS/NIR binned into RGB but with overlay showing camouflage detection.
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VIS/NIR: Space Situational Awareness
Spectral imaging can be used to identify satellite material based on reflectivity and color leading to better understanding of satellite functionality and mission.  Image below is of the International Space Station circa 2010 take from Magdalena Ridge Observatory with no atmospheric correction or compensation using first generation VIS/NIR multispectral sensor.
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MWIR: Material Discrimination
Spectral imaging is the art of quantifying the spectral and spatial characteristics of a scene.  One can think of a spectral image as three-dimensional data cube where each pixel from an otherwise broadband image is decomposed into its spectral (many-band) content.  The spectral composition from an object point, reflected and emitted, can be used to discriminate between different materials in the scene.
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LWIR: Disturbed Earth Detection
A spectral image usually consists of a series of monochromatic images, where each mono-chromatic image represents the scene as it would appear when viewed over a limited wavelength band, and each image in the series is centered at a unique wavelength.  SSSC exploits this phenomenon in the LWIR to locate buried mines and IEDs.
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Last Update:  September 2019