Adjacent infrared multitarget detection using robust background estimation

S Kim, KT Kim - Journal of Sensors, 2016 - Wiley Online Library
S Kim, KT Kim
Journal of Sensors, 2016Wiley Online Library
Small target detection is very important for infrared search and track (IRST) problems.
Grouped targets are difficult to detect using the conventional constant false alarm rate
(CFAR) detection method. In this study, a novel multitarget detection method was developed
to identify adjacent or closely spaced small infrared targets. The neighboring targets
decrease the signal‐to‐clutter ratio in hysteresis threshold‐based constant false alarm rate
(H‐CFAR) detection, which leads to poor detection performance in cluttered environments …
Small target detection is very important for infrared search and track (IRST) problems. Grouped targets are difficult to detect using the conventional constant false alarm rate (CFAR) detection method. In this study, a novel multitarget detection method was developed to identify adjacent or closely spaced small infrared targets. The neighboring targets decrease the signal‐to‐clutter ratio in hysteresis threshold‐based constant false alarm rate (H‐CFAR) detection, which leads to poor detection performance in cluttered environments. The proposed adjacent target rejection‐based robust background estimation can reduce the effects of the neighboring targets and enhance the small multitarget detection performance in infrared images by increasing the signal‐to‐clutter ratio. The experimental results of the synthetic and real adjacent target sequences showed that the proposed method produces an upgraded detection rate with the same false alarm rate compared to the recent target detection methods (H‐CFAR, Top‐hat, and TDLMS).
Wiley Online Library
Showing the best result for this search. See all results