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IGARSS
2009
13 years 2 months ago
High Performance Computing for Hyperspectral Image Analysis: Perspective and State-of-the-art
The main purpose of this paper is to describe available (HPC)based implementations of remotely sensed hyperspectral image processing algorithms on multi-computer clusters, heterog...
Antonio Plaza, Qian Du, Yang-Lang Chang
ISCA
2007
IEEE
217views Hardware» more  ISCA 2007»
13 years 4 months ago
Parallel Processing of High-Dimensional Remote Sensing Images Using Cluster Computer Architectures
Hyperspectral sensors represent the most advanced instruments currently available for remote sensing of the Earth. The high spatial and spectral resolution of the images supplied ...
David Valencia, Antonio Plaza, Pablo Martín...
ICDCS
2006
IEEE
13 years 10 months ago
Distributed Computing for Efficient Hyperspectral Imaging Using Fully Heterogeneous Networks of Workstations
Hyperspectral imaging is a new technique which has become increasingly important in many remote sensing applications, including automatic target recognition for military and defen...
Antonio Plaza, Javier Plaza, David Valencia
JPDC
2008
217views more  JPDC 2008»
13 years 4 months ago
Parallel techniques for information extraction from hyperspectral imagery using heterogeneous networks of workstations
Recent advances in space and computer technologies are revolutionizing the way remotely sensed data is collected, managed and interpreted. In particular, NASA is continuously gath...
Antonio J. Plaza
IJHPCA
2008
104views more  IJHPCA 2008»
13 years 4 months ago
Low-Complexity Principal Component Analysis for Hyperspectral Image Compression
Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in co...
Qian Du, James E. Fowler