DocumentCode :
3087455
Title :
Dim point target detection based on novel complex background suppression
Author :
Zhao Fei ; Zhang Zhi-yong ; Lu Huan-zhang
Author_Institution :
Nat. Key Lab. of Autom. Target Recognition (ATR), Nat. Univ. of Defense Technol.(NUDT), Changsha, China
fYear :
2012
fDate :
16-18 Dec. 2012
Firstpage :
45
Lastpage :
51
Abstract :
A novel complex background suppression based dim point target detection algorithm is presented in this study. Comparing with existing spatial-filter-based background suppression algorithms, the nucleus similarity degree (NSD) of each pixel is analyzed first, then the complex background is predicted by fusing results of two different predictors, and the complex background is removed by subtracting the fused prediction result. A thresholding process is performed on the remnant image, and the target trajectories are detected in binary image sequences to confirm the potential targets. Experimental results indicated that the method can predict the heavily cluttered background accurately as well as enhance the point target, and detect target trajectories effectively. Moreover, the pixel-level processing which is time-consuming in the algorithm is suitable for hardware implementation, this makes a feasible way to achieve real time processing in Automatic Target Recognition (ATR) weapon system.
Keywords :
clutter; image fusion; image sequences; infrared imaging; military systems; object detection; real-time systems; spatial filters; weapons; ATR weapon system; NSD; automatic target recognition weapon system; binary image sequences detection; cluttered background; complex background suppression; dim point target detection; fused prediction; hardware implementation; nucleus similarity degree; pixel-level processing; potential targets; real time processing; remnant image; spatial-filter-based background suppression algorithms; target trajectory detection; thresholding process; Signal to noise ratio; background suppression; real-time processing; target detection; trajectory detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
Type :
conf
DOI :
10.1109/CVRS.2012.6421231
Filename :
6421231
Link To Document :
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