You are hereONR Multi-Disciplinary University Research Initiative (MURI) - Model-Based Hyperspectral Exploitation Algorithm Development

ONR Multi-Disciplinary University Research Initiative (MURI) - Model-Based Hyperspectral Exploitation Algorithm Development


Hyperspectral Exploitation Algorithm Development

Sponsor(s): Office of Naval Research (ONR)

Project Description: Hyperspectral data is becoming a critical tool for military planners. The capture of fine spectral information enables the generation of information products which could not be produced using traditional imaging means. The challenge facing hyperspectral technology, as an operational capability, is with conversion of the raw sensor data into a useful information product that is accurate and reliable. Traditional approaches for processing hyperspectral data have largely focused on the use of statistical tools to process a hypercube, with little regard for other data that may describe the physical phenomena under which the data was collected. The long-term goal of this project is to develop a new generation of hyperspectral processing algorithms that take advantage of underlying physics of a scene while utilizing statistical processing techniques to generate valuable information products.

Project Status: The RIT MURI team (RIT, University of California Irvine , Cornell University) iniated research under this MURI in May 2001 and over this period, there has been substantial research progress in validating the utility of physics-based algorithmic approach. This MURI has been a catalyst for the research team to be awarded additional research support from other sponsors. The research results generated by this MURI have been shared to the hyperspectral community through the generation of over 50 peer reviewed journal acticles, presentations at technical conferences, and the publishing of Masters and PhD theses. This project has supported over 15 graduate students, many of whom have graduated or are about to graduate, and will be taking positions in direct support of the defense and intelligence community. The MURI project will be ending on June 30, 2007.


Subtopics

Longwave Temperature/Emissivity Separation and Atmospheric Compensation

In-Water Radiative Transfer Modeling using Photon Mapping and Model-based In-water Target Detection

Suspended Sediment Modeling

Case II Atmospheric Compensation: Simultaneous Aerosol and Water Constituent Retrieval

Hybrid Statistical Geometric Algorithm for Target Detection

John Kerekes
Faculty
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My research involves the modeling and analysis of remote sensing systems, including hyperspectral, SAR, and lidar imaging technologies. Combining statistical and physical approaches, this research aims to advance our understanding of fundamental remote sensing processes.

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