
Proceedings Paper
Active imaging processing technique for sensor data reconstruction and identificationFormat | Member Price | Non-Member Price |
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Paper Abstract
Active imaging (AI) is necessary for measuring parameters of the objects that do not give out or reflect a specific type
of radiation. AI systems offer a number of advantages over passive imaging systems that operate at visible through nearinfrared
wavelengths and usually rely on solar illumination. The reliability and precision of the target identification
depends on how the signal received from a sensor is processed. Often, obstacles or the imperfection of the sensors and
processing electronics cause loss of some of the information. The technique of processes with missing data is suggested
as part of time series prediction and analysis. Thus, the image may be reconstructed even if the necessary data is
partially absent in the input signal. The suggested method reduces the false alarm rate of the target identification.
Results are provided.
Paper Details
Date Published: 23 April 2012
PDF: 10 pages
Proc. SPIE 8398, Optical Pattern Recognition XXIII, 839807 (23 April 2012); doi: 10.1117/12.919857
Published in SPIE Proceedings Vol. 8398:
Optical Pattern Recognition XXIII
David P. Casasent; Tien-Hsin Chao, Editor(s)
PDF: 10 pages
Proc. SPIE 8398, Optical Pattern Recognition XXIII, 839807 (23 April 2012); doi: 10.1117/12.919857
Show Author Affiliations
Andre Sokolnikov, Visual Solutions and Applications (United States)
Published in SPIE Proceedings Vol. 8398:
Optical Pattern Recognition XXIII
David P. Casasent; Tien-Hsin Chao, Editor(s)
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