Abstract – Hyperspectral imaging or imaging spectroscopy is an imaging technology that provides fully registered spatial and high spectral resolution (radiance, reflectance, or emission) information of the scene in the field of view of the sensor in the spatial, spectral and temporal domains. Hyperspectral remote sensing is undergoing a revolution with the appearance and blooming development of imaging spectrometers across a number of platforms such as microscopes, UAV, stand-off, airborne and space-borne systems at different spatial, spectral and temporal scales and resolutions. Exploitation of this data requires models that take advantage of the information across all image domains efficiently. In this talk, we will describe some approaches used to model hyperspectral imagery to integrate spatial and spectral information and their use in developing algorithms for hyperspectral image processing.
Bio – Dr. Miguel Velez-Reyes is the George W. Edwards/El Paso Electric Distinguished Professor in Engineering and Chair of the Electrical and Computer Engineering Department at the University of Texas at El Paso (UTEP) since 2012. He received the BSEE degree from the University of Puerto Rico at Mayagüez (UPRM), in 1985, and the MSEE and PhD degrees from the Massachusetts Institute of Technology (MIT) in 1988, and 1992, respectively. He was a member of the faculty at the Electrical and Computer Engineering in the University of Puerto Rico at Mayaguez (UPRM) from 1992 to 2012. He was the Founding Director of the UPRM Institute for Research in Integrative Systems and Engineering (IRISE). He served in several Lead positions as Associate Director of the NSF Engineering Research Center for Subsurface Sensing and Imaging Systems (CenSSIS) led by Northeastern University, Director of the UPRM Tropical Center for Earth and Space Studies (TCESS), a NASA University Research Center and of the UPRM Laboratory for Applied Remote Sensing and Image Processing (LARSIP). His research interests are in integrating physical models with statistical, and machine-learning approaches for information extraction using remote or minimally intrusive sensing methods. Dr. Velez-Reyes is a Fellow of SPIE, The International Society for Optics and Photonics, and Fellow of the Academy of Arts and Sciences of Puerto Rico. In 1997, and senior Member of IEEE and was a recipient of the PECASE award.
Sponsored by the Laboratory for Analytic Sciences, The Department of Electrical and Computer Engineering, and the Army Research Office.
LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.
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