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Volume 32 Issue 6
Jun.  2010
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Liu Jin, Ji Hong-bing. IR Small Targets Detection Based on Non-homogeneous Background[J]. Journal of Electronics & Information Technology, 2010, 32(6): 1295-1300. doi: 10.3724/SP.J.1146.2009.01083
Citation: Liu Jin, Ji Hong-bing. IR Small Targets Detection Based on Non-homogeneous Background[J]. Journal of Electronics & Information Technology, 2010, 32(6): 1295-1300. doi: 10.3724/SP.J.1146.2009.01083

IR Small Targets Detection Based on Non-homogeneous Background

doi: 10.3724/SP.J.1146.2009.01083
  • Received Date: 2009-08-13
  • Rev Recd Date: 2010-01-25
  • Publish Date: 2010-06-19
  • For lower detection probability problem of small IR targets in a complex non-homogeneous background, an improved M-estimation filtering algorithm based on residual is proposed to suppress background clutters. The algorithm introduces the basic model of M-estimation to predict background, and target pixels and observed noise are considered as the mixed interference of background estimation. It puts forward the correction function c() related to residual to adaptively adjust gain to reduce the abnormal samples influence of background estimation and increases the accuracy of estimation. Meanwhile, the proposed algorithm uses the forget factor to entreat the non-homogeneous background prediction and the robustness is improved. Experimental results on IR images illustrate that the proposed algorithm can not only predict background effectively in non-homogeneous background but preserve targets information to maximum extent. As a result, the proposed algorithm has higher detection probability.
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  • Wang Jing, Bao Shang-qi, and Ralph J F, et al.. Detection of small objects in multi-layered infrared images [C]. Signal and Data Processing of Small Targets, 2008. Proceedings of the SPIE, 2008, 6969: 696905-696905-8.[2]Wemett B D. Automatic target detection using vector quantization error [C]. Automatic Target Recognition XVIII. Proceedings of the SPIE, 2008, 6967: 696712-696712-10.[3]宗思光, 王江安. 基于形态学图像融合的目标检测方法 [J]. 光电子激光, 2004, 15(2): 208-211.Zong Si-guang and Wang Jiang-an. Infrared image targets detection based on multi-scale mathematical morphology fusion [J].Journal of OptoelectronicsLaser.2004, 15(2):208-211[4]陈远, 王凌, 冯华君等. 高散射介质后向扩散散射实验的图像预处理 [J]. 光电子激光, 2005, 16(11): 1373-1377.Chen Yuan, Wang Ling, and Feng Hua-jun, et al.. Image pre-processing for diffuse backscattering of polarized light from highly scattering media [J].Journal of OptoelectronicsLaser.2005, 16(11):1373-1377[5]Manolakis D G, Ingle V K, and Kogon S M. Statistical and Adaptive Signal Processing [M]. Boston: McGraw-Hill Science/Engineering/Math, 1999, Chapter 8.[6]Wang P, Tian J W, and Gao C Q. Infrared small target detection using directional high pass filters based on LS-SVM [J].Electronics Letters.2009, 45(3):156-158[7]Tang Zhen-min and Wang Xin. An efficient algorithm for infrared small target detection [C][J].Second International Conference on Information and Computing Science ICIC0.2009, 2:51-54[8]曹瑛, 李志永, 卢晓鹏等. 基于自适应领域双边滤波的点目标检测预处理算法[J].电子与信息学报.2008, 30(8):1909-1912浏览Cao Ying, Li Zhi-yong, and Lu Xiao-peng, et al.. A preprocessing algorithm of point target detection based on temporal-spatial bilateral filter using adaptive neighborhoods [J].Journal of Electronics Information Technology.2008, 30(8):1909-1912[9]Huber P J and Ronchetti E M. Robust Statistics (2nd Ed.) [M]. New York: Wiley, 2009, Chapter 3.[10]Haykin S. Adaptive Filter Theory (4th Ed.) [M]. US, Prentice Hall, 2001, Chapter 8.[11]罗军辉, 姬红兵, 刘靳. 一种基于空间滤波的红外小目标检测算法及其应用[J]. 红外与毫米波学报, 2007, 26(3): 209-212.Luo Jun-hui, Ji Hong-bing, and Liu Jin. Algorithm of IR small targets detection based on spatial filter and its application [J]. Journal of Infrared and Millimeter-wave, 2007, 26(3): 209-212.[12]Braga-Neto U, Choudhary M, and Goutsias J. Automatic target detection and tracking in forward-looking infrared image sequences using morphological connected operators [J].Journal of Electronic Imaging.2004, 13(4):802-813
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