John Kerekes


Multi- and hyperspectral imaging systems have found utility in a variety of earth remote sensing applications. Much research has focused on developing new ways to process the data and obtain improved results in a given application. However, relatively little research has focused on the open question of what is the optimum performance possible in a given situation. The work discussed in this paper is aimed at exploring that question through analytical modeling and performance trade studies. We show example analysis results that indicate performance floors where no further improvement is possible due to improved spatial resolution or signal-to-noise ratios in given analysis tasks.

Date of creation, presentation, or exhibit



Proceedings of the 2006 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2006 "Parameter Studies for Spectral Imager Application Performace," Proceedings of the 2006 IEEE International Geoscience and Remote Sensing Symposium (IGARRS). Institute of Electrical and Electronics Engineers. Held at Colorado Convention Center: Denver, Colorado 31 July-4 August, 2006. ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Conference Proceeding

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


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