Adaptive feature-specific imaging

Mark A. Neifeld; Pawan K. Baheti

doi:10.1117/12.826257

21 August 2009 Adaptive feature-specific imaging

Mark A. Neifeld, Pawan K. Baheti

Proceedings Volume 7468, Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems; 746807 (2009) https://doi.org/10.1117/12.826257
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Feature-specific imaging (FSI) is a method by which non-traditional projections of object space may be computed directly in the optical domain. The resulting feature-specific measurements provide the advantages of reduced hardware complexity and improved measurement SNR. This SNR advantage translates into improved task (e.g., target recognition and/or tracking) performance. Adaptive FSI refers to any FSI system for which the results of previous measurements are used to determine future measurement basis vectors. This paper will describe an adaptive FSI system based on the sequential hypothesis testing approach. We will quantify the benefits of adaptation for a M-class recognition task, and present an extension of the AFSI system to incorporate null hypothesis.

Citation Download Citation

Mark A. Neifeld and Pawan K. Baheti "Adaptive feature-specific imaging", Proc. SPIE 7468, Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems, 746807 (21 August 2009); https://doi.org/10.1117/12.826257

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