Results 291 to 300 of about 107,679 (337)

Hyperspectral image data analysis

IEEE Signal Processing Magazine, 2002
The fundamental basis for space-based remote sensing is that information is potentially available from the electromagnetic energy field arising from the Earth's surface and, in particular, from the spatial, spectral, and temporal variations in that field.
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Resolution enhancement of hyperspectral data

Proceedings, IEEE Aerospace Conference, 2003
Hyperspectral imaging systems are assuming a greater importance for a wide variety of commercial and military systems. The reason for this increased interest is the fact that a hyperspectral sensor of a given spatial resolution or pixel size will reveal information on the scene that are not obtainable by single band or multi-spectral sensors.
M.E. Winter, E.M. Winter
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Noise constrained hyperspectral data compression

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), 2002
Hyperspectral data present significant challenges to downlinking, processing, and exploitation. Adaptive linear unmixing compression algorithms exploit spectral correlation to produce high compression ratios with little to no loss of significant information content.
S.T. Rupert, M.H. Sharp, J.N. Sweet, E.J. Cincotta   +3 more
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Robust classification of hyperspectral data

IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004
High dimensionality and highly correlated features are two important characteristics of hyperspectral data that leads to poor performance of conventional classification methods. Furthermore, hyperspectral sensors usually provide relatively low optical resolution, which implies that pixels are bound to cover a mixture of objects with different ...
A. Berge, A.S. Solberg
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Signal Processing for Hyperspectral Data

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
Hyperspectral data form a data-cube consisting of images of an object collected at several hundred, closely spaced wavelengths. They have been found to be of significant potential benefit in areas such as remote sensing of the Earth, medicine, and non-destructive evaluation.
P.K. Varshney, M.K. Arora, R.M. Rao
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Sonification of hyperspectral image data

SPIE Proceedings, 2007
There are many reconnaissance tasks which involve an image analyst viewing data from hyperspectral imaging systems and attempting to interpret it. Hyperspectral image data is intrinsically hard to understand, even when armed with mathematical knowledge and a range of current processing algorithms.
Mark Bernhardt, Catherine Cowell, William Oxford   +2 more
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Thermal infrared hyperspectral data compression

SPIE Proceedings, 1998
Hyperspectral imagers sample the electromagnetic spectrum at greater resolution than more traditional imaging systems, which result in a higher band-to-band correlation and greater amounts of data. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very
Bernard V. Brower, Austin Lan, Rulon E. Simmons, David H. Haddock   +3 more
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Application of Hyperspectral Data

2016
Three decades of airborne imaging spectroscopy have demonstrated the added value of this remote sensing technique to improve the understanding of Earth’s functioning. With the advent of airborne imaging spectroscopy, the specialized image processing system has made the generation of quantitative methods such as semi-analytical and analytical methods ...
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Hyperspectral Data Compression Tradeoff

2011
Hyperspectral data are a challenge for data compression. Several factors make the constraints particularly stringent and the challenge exciting. First is the size of the data: as a third dimension is added, the amount of data increases dramatically making the compression necessary at different steps of the processing chain.
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Interpretation of Hyperspectral Image Data

1999
The data produced by the imaging spectrometers of Section 1.4.6 is different from that of multispectral instruments owing to the enormous number of wavebands recorded — leading to the term hyperspectrdl. For a given geographical area imaged, the data produced can be viewed as a cube, as shown in Fig.
John A. Richards, Xiuping Jia
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