Full Spectral Imaging
Encyclopedia
Full spectral imaging is a form of Imaging spectroscopy
and is the successor to Hyperspectral imaging
. Full Spectral Imaging was developed to improve the capabilities of Earth remote sensing
(see also remote sensing
). Hyperspectral imaging acquires data as many contiguous spectral bands. Full Spectral Imaging (FSI) acquires data as spectral curves. A significant advantage of FSI over Hyperspectral is a significant reduction in data rate and volume. FSI extracts and saves only the information that is in the raw data. The information is contained in the shape of the spectral curves. The rate at which data is produced by an FSI system is proportional to the amount of information in the scene/image.
Full Spectral Imaging, along with Empirical reflectance retrieval
and Autonomous Remote Sensing are the components of the New System for Remote Sensing. The New System for Remote Sensing could be the successor to the Landsat series of satellites of the Landsat program
. The concepts mentioned above have been developed in collaboration with many experts, most of whom have little to nothing to do with traditional remote sensing. These concepts rely solely on currently available off-the-shelf technology, and on existing infrastructure.
Imaging spectroscopy
Imaging spectroscopy is similar to color photography, but each pixel acquires many bands of light intensity data from the spectrum, instead of just the three bands of the RGB color model...
and is the successor to Hyperspectral imaging
Hyperspectral imaging
Hyperspectral imaging collects and processes information from across the electromagnetic spectrum. Much as the human eye sees visible light in three bands , spectral imaging divides the spectrum into many more bands...
. Full Spectral Imaging was developed to improve the capabilities of Earth remote sensing
Earth remote sensing
Earth remote sensing is data collection on the environment, geology, climate, and other characteristics of the Earth by means of sensors positioned in the air or in Earth orbit. Sensors used for this type of data gathering include those covering all parts of the electromagnetic spectrum. Both...
(see also remote sensing
Remote sensing
Remote sensing is the acquisition of information about an object or phenomenon, without making physical contact with the object. In modern usage, the term generally refers to the use of aerial sensor technologies to detect and classify objects on Earth by means of propagated signals Remote sensing...
). Hyperspectral imaging acquires data as many contiguous spectral bands. Full Spectral Imaging (FSI) acquires data as spectral curves. A significant advantage of FSI over Hyperspectral is a significant reduction in data rate and volume. FSI extracts and saves only the information that is in the raw data. The information is contained in the shape of the spectral curves. The rate at which data is produced by an FSI system is proportional to the amount of information in the scene/image.
Full Spectral Imaging, along with Empirical reflectance retrieval
Empirical reflectance retrieval
Empirical reflectance retrieval is a technique in satellite imaging for determining the reflectance of unknown targets by comparison with those areas whose reflectance is independently known....
and Autonomous Remote Sensing are the components of the New System for Remote Sensing. The New System for Remote Sensing could be the successor to the Landsat series of satellites of the Landsat program
Landsat program
The Landsat program is the longest running enterprise for acquisition of satellite imagery of Earth. On July 26, 1972 the Earth Resources Technology Satellite was launched. This was eventually renamed to Landsat. The most recent, Landsat 7, was launched on April 15, 1999. The instruments on the...
. The concepts mentioned above have been developed in collaboration with many experts, most of whom have little to nothing to do with traditional remote sensing. These concepts rely solely on currently available off-the-shelf technology, and on existing infrastructure.