Volume 16 Issue 3
May  2023
Turn off MathJax
Article Contents
SU De-zhi, LIU Liang, WANG Kun, WU Shi-yong, LIU Ling-shun, MING Rui-long, GONG Jian. Sea-sky-line detection method based on polarization difference images[J]. Chinese Optics, 2023, 16(3): 596-606. doi: 10.37188/CO.2022-0181
Citation: SU De-zhi, LIU Liang, WANG Kun, WU Shi-yong, LIU Ling-shun, MING Rui-long, GONG Jian. Sea-sky-line detection method based on polarization difference images[J]. Chinese Optics, 2023, 16(3): 596-606. doi: 10.37188/CO.2022-0181

Sea-sky-line detection method based on polarization difference images

Funds:  Supported by The National Natural Science Foundation of China (No. 61205206)
More Information
  • Corresponding author: liul513@126.com
  • Received Date: 17 Aug 2022
  • Rev Recd Date: 06 Sep 2022
  • Accepted Date: 02 Nov 2022
  • Available Online: 19 Nov 2022
  • Aiming at the problem of sea-sky-line detection in low-contrast infrared images being difficult and easily affected by interference factors such as clouds, strip waves and sea clutter, we propose a method of using polarization difference images for sea-sky-line detection. Firstly, Polarization Difference Imaging (PDI) is used to enhance the local contrast of the sea surface area and the Signal-to-Noise Ratio (SNR) of the sea-sky-line. A large-scale local contrast accumulation method of the polarization difference images is then used to determine the sea-sky-line area. Finally, the accurate detection of a small-scale sea-sky-line is completed by combining the gradient significance and polynomial fitting in the sea-sky-line area. Overall, the methodology integrates multi-dimensional information such as the Degree of Linear Polarization (DOLP) and the Angle of Polarization (AOP) for sea-sky-line detection, and combines large-scale and small-scale detection, which can effectively overcome interference of factors such as clouds, strip waves and sea clutter. The experimental results show that the accuracy of this algorithm for sea-sky-line detection is 98.5%, and the average time consumed is 16 ms. The experimental results indicate that the proposed algorithm can realize fast and accurate sea-sky-line detection so it has wide applicability in different scenes.

     

  • loading
  • [1]
    冯天伟, 刘金清, 肖金超, 等. 海天线检测方法研究综述[J]. 激光与光电子学进展,2020,57(16):160002.

    FENG T W, LIU J Q, XIAO J CH, et al. Sea-sky line detection methods: an overview[J]. Laser &Optoelectronics Progress, 2020, 57(16): 160002. (in Chinese)
    [2]
    韩嘉隆, 毛征, 王宁, 等. 基于二维OTSU的海天分界线提取算法[J]. 国外电子测量技术,2016,35(8):67-70. doi: 10.3969/j.issn.1002-8978.2016.08.015

    HAN J L, MAO ZH, WANG N, et al. Algorithm for sea-sky-line extraction based on two-dimension OTSU[J]. Foreign Electronic Measurement Technology, 2016, 35(8): 67-70. (in Chinese) doi: 10.3969/j.issn.1002-8978.2016.08.015
    [3]
    张志祥, 王秋萍, 朱旭芳, 等. 基于场景划分的海天线检测方法[J]. 华中科技大学学报(自然科学版),2020,48(8):61-66.

    ZHANG ZH X, WANG Q P, ZHU X F, et al. Sea-sky line detection method based on scene division[J]. Journal of Huazhong University of Science and Technology (Nature Science Edition), 2020, 48(8): 61-66. (in Chinese)
    [4]
    戴永寿, 刘博文, 李立刚, 等. 基于局部Otsu分割与Hough变换的海天线检测[J]. 光电工程,2018,45(7):180039.

    DAI Y SH, LIU B W, LI L G, et al. Sea-sky-line detection based on local Otsu segmentation and Hough transform[J]. Opto-Electronic Engineering, 2018, 45(7): 180039. (in Chinese)
    [5]
    KONG X Y, LIU L, QIAN Y SH, et al. Automatic detection of sea-sky horizon line and small targets in maritime infrared imagery[J]. Infrared Physics &Technology, 2016, 76: 185-199.
    [6]
    徐良玉, 马录坤, 谢燮, 等. 基于结构森林边缘检测和Hough变换的海天线检测[J]. 上海大学学报(自然科学版),2017,23(1):47-55.

    XU L Y, MA L K, XIE X, et al. Sea-sky line detection based on structured forests edge detection and Hough transform[J]. Journal of Shanghai University (Natural Science), 2017, 23(1): 47-55. (in Chinese)
    [7]
    曾文静, 万磊, 张铁栋, 等. 基于海面可见光图像的海界线快速检测[J]. 光学学报,2012,32(1):0111001. doi: 10.3788/AOS201232.0111001

    ZENG W J, WAN L, ZHANG T D, et al. Fast detection of sea line based on the visible characteristics of marine images[J]. Acta Optica Sinica, 2012, 32(1): 0111001. (in Chinese) doi: 10.3788/AOS201232.0111001
    [8]
    王博, 苏玉民, 万磊, 等. 基于梯度显著性的水面无人艇的海天线检测方法[J]. 光学学报,2016,36(5):0511002. doi: 10.3788/AOS201636.0511002

    WANG B, SU Y M, WAN L, et al. Sea sky line detection method of unmanned surface vehicle based on gradient saliency[J]. Acta Optica Sinica, 2016, 36(5): 0511002. (in Chinese) doi: 10.3788/AOS201636.0511002
    [9]
    WANG B, SU Y M, WAN L. A sea-sky line detection method for unmanned surface vehicles based on gradient saliency[J]. Sensors, 2016, 16(4): 543. doi: 10.3390/s16040543
    [10]
    董宇星, 刘伟宁. 基于灰度特性的海天背景小目标检测[J]. 中国光学与应用光学,2010,3(3):252-256.

    DONG Y X, LIU W N. Detection of sea-sky line in complicated background based on grey characteristics[J]. Chinese Journal of Optics, 2010, 3(3): 252-256. (in Chinese)
    [11]
    刘士建, 吴滢跃, 蔡能斌. 低SNR海天线提取算法[J]. 红外与激光工程,2013,42(12):3491-3495. doi: 10.3969/j.issn.1007-2276.2013.12.059

    LIU SH J, WU Y Y, CAI N B. Novel low-SNR sea-sky-line extraction algorithm[J]. Infrared and Laser Engineering, 2013, 42(12): 3491-3495. (in Chinese) doi: 10.3969/j.issn.1007-2276.2013.12.059
    [12]
    李林丰, 田甜, 沙漠洲, 等. 基于局部熵滤波和梯度累积的海天线检测方法[J]. 华中科技大学学报(自然科学版),2021,49(11):47-52.

    LI L F, TIAN T, SHA M ZH, et al. Sea-sky line detection method based on local entropy filtering and gradient accumulation[J]. Journal of Huazhong University of Science and Technology (Nature Science Edition), 2021, 49(11): 47-52. (in Chinese)
    [13]
    林昌. 大雾下海上图像的目标分离与智能辨识研究[D]. 厦门: 集美大学, 2021.

    LIN CH. Research on target separation and intelligent recognition of maritime images under fog[D]. Xiamen: Jimei University, 2021. (in Chinese)
    [14]
    宫剑, 吕俊伟, 刘亮, 等. 红外偏振图像的舰船目标检测[J]. 光谱学与光谱分析,2020,40(2):586-594.

    GONG J, LÜ J W, LIU L, et al. Ship target detection based on infrared polarization image[J]. Spectroscopy and Spectral Analysis, 2020, 40(2): 586-594. (in Chinese)
    [15]
    宫剑, 吕俊伟, 刘亮, 等. 红外偏振舰船目标自适应尺度局部对比度检测[J]. 光学 精密工程,2020,28(1):223-233. doi: 10.3788/OPE.20202801.0223

    GONG J, LV J W, LIU L, et al. Adaptive scale local contrast detection for infrared polarization ship targets[J]. Optics and Precision Engineering, 2020, 28(1): 223-233. (in Chinese) doi: 10.3788/OPE.20202801.0223
    [16]
    赵如雪. 基于偏振差分成像的浑浊介质中目标检测方法研究[D]. 南京: 南京理工大学, 2020.

    ZHAO R X. Research on target detection method in turbid media based on polarization difference imaging[D]. Nanjing: Nanjing University of Science and Technology, 2020. (in Chinese)
    [17]
    张玉鑫. 基于全偏振信息探测的海空背景图像去雾关键技术研究[D]. 长春: 中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2020.

    ZHANG Y X. Research on key technologies of haze removal of sea-sky background image based on full polarization information detection[D]. Changchun: University of Chinese Academy of Sciences (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences), 2020. (in Chinese)
    [18]
    汪杰君, 梁磊, 李树, 等. 水下目标偏振差分成像模型修正与实现[J]. 光学学报,2019,39(11):1111003. doi: 10.3788/AOS201939.1111003

    WANG J J, LIANG L, LI SH, et al. Correction and implementation of polarization-difference imaging model for underwater target[J]. Acta Optica Sinica, 2019, 39(11): 1111003. (in Chinese) doi: 10.3788/AOS201939.1111003
    [19]
    韩裕生, 周浦城, 乔延利, 等. 基于最小互信息的自适应偏振差分成像方法[J]. 红外与激光工程,2011,40(3):487-491. doi: 10.3969/j.issn.1007-2276.2011.03.022

    HAN Y SH, ZHOU P CH, QIAO Y L, et al. Adaptive polarization difference imaging approach based on minimum mutual information[J]. Infrared and Laser Engineering, 2011, 40(3): 487-491. (in Chinese) doi: 10.3969/j.issn.1007-2276.2011.03.022
    [20]
    宿德志, 刘亮, 吴世永, 等. 辐射耦合效应对目标红外偏振特性的影响[J]. 中国光学(中英文), 2023, 16(2): 318-328.

    SU D ZH, LIU L, WU SH Y, et al. . Influence of radiation coupling effect on polarization characteristics of targets[J]. Chinese Optics, 2023, 16(2): 318-328. (in Chinese)
    [21]
    柳祎, 史浩东, 姜会林, 等. 粗糙目标表面红外偏振特性研究[J]. 中国光学,2020,13(3):459-471. doi: 10.3788/CO.2019-0123

    LIU Y, SHI H D, JIANG H L, et al. Infrared polarization properties of targets with rough surface[J]. Chinese Optics, 2020, 13(3): 459-471. (in Chinese) doi: 10.3788/CO.2019-0123
    [22]
    LIU H ZH, SHI Z L, FENG B. An infrared DoLP computational model considering surrounding irradiance[J]. Infrared Physics &Technology, 2019, 106: 103043.
    [23]
    王琪, 梁静秋, 梁中翥, 等. 分孔径红外偏振成像仪光学系统设计[J]. 中国光学,2018,11(1):92-99. doi: 10.3788/CO.20181101.0092

    WANG Q, LIANG J Q, LIANG ZH ZH, et al. Design of decentered aperture-divided optical system of infrared polarization imager[J]. Chinese Optics, 2018, 11(1): 92-99. (in Chinese) doi: 10.3788/CO.20181101.0092
    [24]
    张景华. 基于红外偏振信息的海面杂波抑制及舰船目标识别技术[D]. 长沙: 国防科技大学, 2018.

    ZHANG J H. Research on sea clutter suppression and ship target detection based on infrared polarization information[D]. Changsha: National University of Defense Technology, 2018. (in Chinese)
    [25]
    张景华, 张焱, 石志广. 基于长波红外的海面场景偏振特性分析与建模[J]. 红外与毫米波学报,2018,37(5):586-594. doi: 10.11972/j.issn.1001-9014.2018.05.011

    ZHANG J H, ZHANG Y, SHI ZH G. Study and modeling of infrared polarization characteristics based on sea scene in long wave band[J]. Journal of Infrared and Millimeter Waves, 2018, 37(5): 586-594. (in Chinese) doi: 10.11972/j.issn.1001-9014.2018.05.011
    [26]
    ZHANG J H, ZHANG Y, SHI ZH G. Long-wave infrared polarization feature extraction and image fusion based on the orthogonality difference method[J]. Journal of Electronic Imaging, 2018, 27(2): 023021.
    [27]
    COOK R L, TORRANCE K E. A reflectance model for computer graphics[J]. ACM SIGGRAPH Computer Graphics, 1981, 15(3): 307-316. doi: 10.1145/965161.806819
    [28]
    仇荣超, 吕俊伟, 宫剑, 等. 前视红外图像中海岸线与海天线的通用检测方法研究[J]. 兵工学报,2019,40(6):1171-1178. doi: 10.3969/j.issn.1000-1093.2019.06.007

    QIU R CH, LÜ J W, GONG J, et al. Research on general detection method of coastline and sea-sky line in FLIR Image[J]. Acta Armamentarii, 2019, 40(6): 1171-1178. (in Chinese) doi: 10.3969/j.issn.1000-1093.2019.06.007
    [29]
    杨章含, 曾培峰. 基于MSER的弹孔识别算法的研究[J]. 信息技术与网络安全,2019,38(3):24-29.

    YANG ZH H, ZENG P F. A research on bullet holes recognition algorithm based on MSER[J]. Information Technology and Network Security, 2019, 38(3): 24-29. (in Chinese)
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(2)

    Article views(602) PDF downloads(269) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return