John Kerekes Headshot

John Kerekes

Research Professor

Chester F. Carlson Center for Imaging Science
College of Science

585-475-6996
Office Hours
Upon request.
Office Location
Office Mailing Address
3242 Carlson (Building 76)

John Kerekes

Research Professor

Chester F. Carlson Center for Imaging Science
College of Science

Education

BS, MS, Ph.D., Purdue University

Bio

Dr. Kerekes has worked throughout his career on advancing the state of the art and practice of remote sensing technology through theoretical investigations, data analyses, and modeling of remote sensing systems. His interest has been in viewing the end-to-end remote sensing process as a system with application performance as the system metric. Developing models with this perspective has improved understanding of parameter sensitivities and requirements for system design and operation. His work has emphasized the use of statistical parametric models in propagating the information bearing characteristics of the scene through the effects of the remote sensing process. He has applied this approach to the study of multispectral remote sensing systems designed for surface land cover classification, the vertical profiling of atmospheric temperature and water vapor, the sensing of surface particulate matter and for unresolved (sub-pixel) object detection and identification. He has also investigated the use of spectral imaging for medical applications.

585-475-6996

Areas of Expertise

Select Scholarship

Journal Paper
Canas, Chase and John Kerekes. "Design and Demonstration of a Lattice-Based Target for Hyperspectral Subpixel Target Detection Experiments." IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 62. (2024): 1-10. Web.
Zimmerman, Lucy and John Kerekes. "Comparison of Methane Detection Using Shortwave and Longwave Infrared Hyperspectral Sensors Under Varying Environmental Conditions." IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 16. (2023): 2517-2531. Print.
Prox, Lauren, et al. "Integrating Satellite and Sensor Measurements to Understand Urban Air Quality: A Case Study of PM2.5 in Asunción, Paraguay." EM: The Magazine for Environmental Managers. (2022): 1-7. Web.
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Published Conference Proceedings
Canas, Chase, John Kerekes, and Scott Brown. "Multivariate methods to explore system sensitivities for hyperspectral subpixel target detection." Proceedings of the Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXX. Ed. Miguel Velez-Reyes and David Messinger. National Harbor, MD: SPIE, 2024. Web.
Zimmerman, Lucy and John Kerekes. "Comparison of methane detection for shortwave and longwave infrared hyperspectral sensors under varying environmental conditions." Proceedings of the Imaging Spectrometry XXV: Applications, Sensors, and Processing. Ed. Emmett Ientilucci and Christine Bradley. San Diego, CA: SPIE, 2022. Web.
Maloney, Colin, et al. "Linear Mixing Model Performance with Nonlinear Effects in Hyperspectral Sub-Pixel Target Detection." Proceedings of the IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. Ed. David Kunkee and Rashmi Shah. Pasadena, CA: IEEE, 2023. Web.
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Full Patent
Katuwal, Gajendra, et al. "Automated Fundus Image Field Detection and Quality Assessment." U.S. Patent 9,905,008. 27 Feb. 2018.
Published Article
Matteoli, S., E.J. Ientilucci, J.P. Kerekes. “Operational andperformance considerations of radiativetransfer modeling in hyperspectral target detection.” IEEE Transactions on Geoscience and Remote Sensing, (2010): 1-13. Print. £
Stefanou, M.S., J.P. Kerekes. “Image-Derived Predictionof Spectral Image Utility for Target DetectionApplications.” IEEE Transactions on Geoscience and Remote Sensing, 48.5 (2010): 1827-1833. Print. "  £
King, K.C., J.P. Kerekes. “Development of a Web-based Blind Test to Score and Rank Hyperspectral Classification Algorithms.” Proceedings of the 2010 Western NY Image Processing Workshop, IEEE, Nov. 2010. n.p. Print. "  £
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Currently Teaching

IMGS-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-791
0 Credits
Continuation of Thesis
IMGS-799
1 - 4 Credits
This course is a faculty-directed tutorial of appropriate topics that are not part of the formal curriculum. The level of study is appropriate for student in their graduate studies.
IMGS-890
1 - 6 Credits
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-891
0 Credits
Continuation of Thesis

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