Active imaging processing technique for sensor data reconstruction and identification

Andre Sokolnikov

doi:10.1117/12.919857

23 April 2012 Active imaging processing technique for sensor data reconstruction and identification

Andre Sokolnikov

Proceedings Volume 8398, Optical Pattern Recognition XXIII; 839807 (2012) https://doi.org/10.1117/12.919857
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Andre Sokolnikov "Active imaging processing technique for sensor data reconstruction and identification", Proc. SPIE 8398, Optical Pattern Recognition XXIII, 839807 (23 April 2012); https://doi.org/10.1117/12.919857

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available