A Novel and High-Speed Local Contrast Method for Infrared Small-Target Detection

被引：13

作者：

Wang, Hao ^{[1
,2
]}

Liu, Chuntong ^{[3
]}

Ma, Chenning ^{[1
]}

Ma, Shixin ^{[3
]}

机构：

[1] Beijing Inst Remote Sensing Equipment, Beijing 100854, Peoples R China

[2] PLA Rocket Force Univ Engn, Xian 710025, Peoples R China

[3] PLA Rocket Force Univ Engn, Photoelect Protect Teaching & Res Sect, Xian 710025, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2020年 / 17卷 / 10期

关键词：

Clutter; Indexes; Object detection; Real-time systems; Remote sensing; Programmable logic arrays; Rockets; Improved local contrast measure (ILCM); infrared (IR) image; novel high-boost filter (NHBF); target detection;

D O I：

10.1109/LGRS.2019.2951918

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Robust and effective small-target detection in infrared (IR) imagery has significant implications for modern military operations. For the objective of achieving simultaneous solid performance in detection rate, false alarm rate (FAR), and speed, this research provides a novel method making use of local contrast measure (LCM) based on high-boost filters [novel high-boost filter improved LCM (NHBF-ILCM)]. First, a novel high-boost filter is used for target signal enhancement and background clutter suppression, followed by an ILCM used to achieve high-speed local contrast and further target resolution enhancement and clutter suppression. Then, an adaptive threshold is used to segment the target. Finally, through experiments using three sequences with different and typically complex backgrounds, the detection capabilities of the proposed method are confirmed, and these results reveal that the proposed algorithm is able to achieve the best performance and highest efficiency for real IR small-target detection applications among similar algorithms.

引用

页码：1812 / 1816

页数：5

共 14 条

[1] New class of top-hat transformation to enhance infrared small targets [J].

Bai, Xiangzhi ;

Zhou, Fugen ;

Xie, Yongchun .

JOURNAL OF ELECTRONIC IMAGING, 2008, 17 (03)

[2] A Local Contrast Method for Small Infrared Target Detection [J].

Chen, C. L. Philip ;

Li, Hong ;

Wei, Yantao ;

Xia, Tian ;

Tang, Yuan Yan .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (01) :574-581

[3] Small Infrared Target Detection Using Sparse Ring Representation [J].

Gao, Chengqiang ;

Zhang, Tianqi ;

Li, Qiang .

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE, 2012, 27 (03) :21-30

[4] Infrared Patch-Image Model for Small Target Detection in a Single Image [J].

Gao, Chenqiang ;

Meng, Deyu ;

Yang, Yi ;

Wang, Yongtao ;

Zhou, Xiaofang ;

Hauptmann, Alexander G. .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (12) :4996-5009

[5] A Robust Infrared Small Target Detection Algorithm Based on Human Visual System [J].

Han, Jinhui ;

Ma, Yong ;

Zhou, Bo ;

Fan, Fan ;

Liang, Kun ;

Fang, Yu .

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2014, 11 (12) :2168-2172

[6] Small Target Detection Utilizing Robust Methods of the Human Visual System for IRST [J].

Kim, Sungho ;

Yang, Yukyung ;

Lee, Joohyoung ;

Park, Yongchan .

JOURNAL OF INFRARED MILLIMETER AND TERAHERTZ WAVES, 2009, 30 (09) :994-1011

[7]

LI F, 2012, OPT OPTOELECTRON TEC, V10, P28

[8] Infrared and visible image fusion via gradient transfer and total variation minimization [J].

Ma, Jiayi ;

Chen, Chen ;

Li, Chang ;

Huang, Jun .

INFORMATION FUSION, 2016, 31 :100-109

[9] Effective Infrared Small Target Detection Utilizing a Novel Local Contrast Method [J].

Qin, Yao ;

Li, Biao .

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2016, 13 (12) :1890-1894

[10] High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection [J].

Shi, Yafei ;

Wei, Yantao ;

Yao, Huang ;

Pan, Donghui ;

Xiao, Guangrun .

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (01) :33-37

← 1 2 →