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Ship Target Detection Based on Infrared Polarization Image |
GONG Jian, LÜ Jun-wei, LIU Liang, QIU Rong-chao |
Naval Aviation University, Yantai 264000, China |
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Abstract As an important method detecting ship targets, infrared imaging system plays a vital role in military reconnaissance. In the face of complex background, bad weather environment, etc., the local contrast of target and background is low, which causes that the performance indicators of infrared system such as detection accuracy and recall rate are seriously affected. Considering the above problems, the research on ship target detection method based on infrared polarization image is carried out. Through the long-wave uncooled infrared polarization image acquisition system, 86 sets of infrared polarization images with 4 polarization directions (0°,45°,90°,135° ) were collected, and 309 ship targets were sampled. For the infrared polarization image with different polarization directions, the target and background local contrast of the infrared intensity/polarization image in the same scene, it was found that the difference between the sea surface and the ship target polarization characteristics can effectively improve the target and background local contrast. In the forward-looking infrared image, the ship target is usually located near or below the sea-sky line, but the complex background and weather and other factors have a great influence on the detection of the sea-sky line in the infrared image. For this reason, the infrared polarization image sea-sky line detection method is proposed. Gaussian filtering is used to eliminate the local extremum in the histogram of polarization image. According to the difference of the polarization characteristics between the sea and the background, the sea-sky line is detected by the bimodal method threshold segmentation. Finally, the sea-sky line is detected by the Hough transform, and the sea surface is segmented as the target candidate region. Aiming at the problem that the infrared polarization image is seriously interfered by sea clutter, the sea clutter background suppression algorithm is proposed. The background suppression and distance weighting method are used to suppress the complicated sea clutter background in the polarization image. Finally, the ship targets are detected according to the MSER algorithm, after they are constrained basing on the characteristics of the ship target. The ship target detection experiment is carried out on 86 sets of infrared polarization images. The proposed method can effectively overcome the interference of complex background, sea clutter and other factors to accurately detect the sea-sky line, and the detection precision ratio and the recall ratio are 93.2% and 95.7%, respectively, which is better than the infrared ship target detection method, especially in the scene with the low contrast of infrared image. Obviously, the detection precision ratio and the recall ratio increase by 46.5% and 16.4%, respectively. The research results show that considering the difference of polarization characteristics between the ship target and the background in the infrared polarization image can effectively improve the local contrast between the target and the background, which is conducive to accurately detecting the sea-sky line, improving the ship detection precision ratio and the recall ratio, and complex background. It has strong adaptability to complex background and bad weather, which has great application value in military applications. This study has great significance for the development of ship target detection technology in the infrared band.
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Received: 2018-11-26
Accepted: 2019-04-27
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[1] Fang L, Wang X, Wan Y. Journal of Electronic Imaging, 2016, 25(4): 041010.
[2] QI Sheng-xiang, XU Guo-jing, WU Jian-min, et al(漆昇翔, 徐国靖, 吴建民, 等). Journal of Huazhong University of Science & Technology·Natural Science Edition(华中科技大学学报·自然科学版), 2017, 45(11): 29.
[3] LIU Feng, SHEN Tong-sheng, GUO Shao-jun, et al(刘 峰, 沈同圣, 郭少军, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2017, 37(6): 1934.
[4] ZHAO Wei, HUI Bin, ZHANG Yu-xiao(赵 微, 惠 斌, 张玉晓). Infrared Laser Eng.(红外与激光工程), 2014, 43(1): 48.
[5] Li S, Jin W, Xia R, et al. Optics Express, 2016, 24(23): 26414.
[6] ZHANG Qiao, SUN Xiao-bing, HONG Jin, et al(张 荞,孙晓兵,洪 津, 等). J. Infrared Millim W.(红外与毫米波学报), 2013, 32(6): 502.
[7] Zhao H, Ji Z, Zhang Y, et al. Optics Express, 2016, 24(15): 16396.
[8] WANG Xia, LIANG Jian-an, LONG Hua-bao, et al(王 霞, 梁建安, 龙华宝, 等). Infrared Laser Eng.(红外与激光工程), 2016, 45(7): 32.
[9] Liang J A, Wang X, Fang Y J, et al. Applied Optics, 2018, 57(16): 4649.
[10] TIAN Chang-hui, CAI Ming, YANG Bai-yu, et al(田昌会, 蔡 明, 杨百愚, 等). Infrared Laser Eng.(红外与激光工程), 2014, 43(3): 737.
[11] LI Gui-xiang, CHAO Shi-yu, SONG Hai-tao, et al(李桂祥, 巢时宇, 宋海涛, 等). Journal of Air Force Radar Academy(空军雷达学院学报) , 2012, 26(3): 178.
[12] Matas J, Chum O, Urban M, et al. Image and Vision Computing, 2004, 22(10): 761.
[13] DU Lan, LIU Bin, WANG Yan, et al(杜 兰, 刘 彬, 王 燕, 等). Journal of Electronics & Information Technology(电子与信息学报), 2016, 38(12): 3018. |
[1] |
QIU Rong-chao1, LOU Shu-li2, LI Ting-jun1, GONG Jian1. Research on Detection of Ship Target at Sea Based on Multi-Spectral Infrared Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(03): 698-704. |
[2] |
CHEN Wei-li1, SUN Qiu-ju2, WANG Shu-hua1, LI Jun-wei1, DONG Yan-bing1, XU Wen-bin1. Influence Analysis of Target Surface Emissivity on Infrared Radiation Polarization Characteristics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(03): 737-742. |
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