The most significant recent breakthrough in remote sensing has been the development of hyperspectral sensors and software to analyze the resulting image data. Fifteen years ago only spectral remote sensing experts had access to hyperspectral images or software tools to take advantage of such images. Over the past decade hyperspectral image analysis has matured into one of the most powerful and fastest growing technologies in the field of remote sensing.
The "hyper" in hyperspectral means "over" as in "too many" and refers to the large number of measured wavelength bands. Hyperspectral images are spectrally overdetermined, which means that they provide ample spectral information to identify and distinguish spectrally unique materials. Hyperspectral imagery provides the potential for more accurate and detailed information extraction than possible with any other type of remotely sensed data.
This paper will review some relevant spectral concepts, discuss the definition of hyperspectral versus multispectral, review some recent applications of hyperspectral image analysis, and summarize image-processing techniques commonly applied to hyperspectral imagery.
"Introduction to Hyperspectral Image Analysis,"
Online Journal of Space Communication: Vol. 2
, Article 8.
Available at: https://ohioopen.library.ohio.edu/spacejournal/vol2/iss3/8
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