FPGA implementation of local contrast method for infrared small target detection - Details

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Abstract：

Infrared　(IR)　small　target　detection　has　become　an　important　technology　in　infrared　searching　and　tracking　system,　infrared　radar　warning　system　and　infrared　imaging　tracking　system.　Among　several　computational　models　we　use　a　local　contrast　method　(LCM)　to　detect　IR　small　target　which　is　inspired　by　human　vision　system　(HVS)　and　derived　kernel　(DK)　model.　This　paper　presents　a　system　architecture　which　employs　a　field-programmable　gate　array　(FPGA)　as　the　hardware　processing　platform　for　small　target　detection　in　infrared　image　at　low　signal-noise　ratio　(SNR).　Performance　of　the　IR　small　target　detection　system　will　be　evaluated　by　performing　several　experiments.　The　platform　based　on　FPGA　will　provide　high　computational　performance　to　satisfy　the　real-time　processing　and　low　power　consumption　requirements.　©　2015　IEEE.

Keyword：

Hardware implementation; IR image; Local contrast; Target detection

Author Community：

[ 1 ] [Bo, M.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Hui, Z.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Zheng, M.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Ang, L.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Wenyang, J.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 6 ] [Weijun, M.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China

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Source ：

2015 IEEE 12th International Conference on Electronic Measurement and Instruments, ICEMI 2015

Year： 2016

Volume： 3

Page： 1293-1297

Language： English

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count： 2

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 8

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信息科学技术学院本学院/部未明确归属的数据

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