搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

浅海被动水下偏振成像探测方法

卫毅 刘飞 杨奎 韩平丽 王新华 邵晓鹏

引用本文:
Citation:

浅海被动水下偏振成像探测方法

卫毅, 刘飞, 杨奎, 韩平丽, 王新华, 邵晓鹏

Passive underwater polarization imaging detection method in neritic area

Wei Yi, Liu Fei, Yang Kui, Han Ping-Li, Wang Xin-Hua, Shao Xiao-Peng
PDF
导出引用
  • 针对传统被动水下偏振成像方法忽略水体对光的吸收效应,成像结果中存在严重的色彩失真,且并未深入发掘利用背景散射光中包含的场景信息的问题.提出浅海被动水下偏振成像探测方法,该方法从水体中背景散射光的传输特性出发,分析场景深度信息与散射光的物理关系,建立基于深度信息的水下Lambertian反射模型,实现无色彩畸变的水下目标场景清晰成像探测.实验结果表明,该方法能够提供接近水下目标真实色彩、符合人眼视觉特性的清晰探测结果,提高水下成像探测能力.
    Underwater imaging is widely applied to mariculture, archaeology, and hydrocarbon exploration, because it can provide the information about visualized target. Among various underwater imaging techniques, polarization imaging is of particular interest to us, due to its simple system structure and low cost. It images the waterbody through using the polarization characteristics of light, specifically, the background light and target light. Active polarization imaging method illuminates a target scene with an artificial polarized light source to provide polarization information for imaging. But in neritic area, active imaging leads to complex light scattering conditions when artificial light and natural light are superimposed together, which further leads to poor image quality. Passive underwater polarization imaging attempts to recover a clear image by utilizing the polarization characteristics of background light and target light. However, serious color cast always appears in the final image, resulting from light absorbed by water, which may further result in target distortion. In this manuscript, we present a passive underwater polarization imaging method for detecting a target in neritic area. A depth-information-based underwater Lambertian reflection model is established by incorporating the depth information into the traditional Lambertian reflection model. First, we attribute the light changes in color and brightness of a Lambertian surface to the spatial variation of the light. According to Lambertian reflection model, the appearance of a target on a detector depends on the light source, the surface reflectance, and the camera sensitivity function. But in underwater imaging, light attenuation at different wavelengths also varies with depth. By analyzing the transmission characteristics of background light in water, we build a physical relationship between the depth information of the scene and the background light. After that, we take the depth information as the weight of light intensity distribution. Then we calculate the product of the light intensity and the camera sensitivity function in the underwater scene according to gray world algorithm, and the real color information of the target can be obtained. Finally, the clear image of an underwater target scene can be obtained, where color cast is calibrated and background light is removed. Underwater experiments are conducted to demonstrate the validity of the proposed method. Besides, the quantitative analyses also verify the improvement of the quality in final target image. Compared with conventional passive underwater polarization imaging methods, the proposed method is capable of detecting targets in various conditions, with the color cast problem solved. It can provide underwater images with better quality and valid detailed information. Furthermore, the proposed method is easy to conduct with no need to change the conventional polarization imaging system and is promising in various practical applications.
      通信作者: 邵晓鹏, xpshao@xidian.edu.cn
    • 基金项目: 国家自然科学基金青年科学基金(批准号:61705175)、中国博士后科学基金(批准号:2017M613063)、中国科学院长春光学精密机械研究所应用光学国家重点实验室基金(批准号:CS16017050001)和中央高校基本科研业务费(批准号:JB170503)资助的课题.
      Corresponding author: Shao Xiao-Peng, xpshao@xidian.edu.cn
    • Funds: Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61705175), the China Postdoctoral Science Foundation (Grant No. 2017M613063), the State Key Laboratory of Optical Technology for Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (Grant No. CS16017050001), and the Fundamental Research Fund for the Central Universities, China (Grant No. JB170503).
    [1]

    Lavest J M, Guichard F, Rousseau C 2002 International Conference on Image Processing Rochester, NY, USA, September 22-25, 2002 p813

    [2]

    Panetta K, Gao C, Agaian S 2016 IEEE J. Oceanic Eng. 41 541

    [3]

    Chennu A, Frber P, De'Ath G, de Beer D, Fabricius K E 2017 Sci. Rep. 7 7122

    [4]

    Chiang J Y, Chen Y C 2012 IEEE Trans. Image Process. 21 1756

    [5]

    Zhao X W, Jin T, Chi H, Qu S 2015 Acta Phys. Sin. 64 104201 (in Chinese) [赵欣慰, 金韬, 池灏, 曲嵩 2015 物理学报 64 104201]

    [6]

    Han P L, Liu F, Zhang G, Tao Y, Shao X P 2018 Acta Phys. Sin. 67 054202 (in Chinese) [韩平丽, 刘飞, 张广, 陶禹, 邵晓鹏 2018 物理学报 67 054202]

    [7]

    Liu F, Cao L, Shao X, Han P L, Bin X 2015 Appl. Opt. 54 8116

    [8]

    Huang B J, Liu T G, Han H F, Han J H, Yu M X 2016 Opt. Express 24 9826

    [9]

    Schechner Y Y, Karpel N 2005 IEEE J. Oceanic Eng. 30 570

    [10]

    Han P L, Liu F, Yang K, Ma J Y, Li J J, Shao X P 2017 Appl. Opt. 56 6631

    [11]

    Schechner Y Y, Averbuch Y 2007 IEEE Trans. Pattern Anal. Mach. Intell. 29 1655

    [12]

    Schechner Y Y, Karpel N 2004 IEEE Computer Vision and Pattern Recognition Washington, USA, June 22-25, 2004 p536

    [13]

    Jaffe J S 2010 Opt. Express 18 12328

    [14]

    Guan J G, Zhu J P, Tian H, Hou X 2015 Acta Phys. Sin. 64 224203 (in Chinese) [管今哥, 朱京平, 田恒, 侯洵 2015 物理学报 64 224203]

    [15]

    Treibitz T, Schechner Y Y 2009 IEEE Trans. Pattern Anal. Mach. Intell. 31 385

    [16]

    Liu F, Shao X, Gao Y, Xiang L B, Han P L, Li G 2016 J. Opt. Soc. Am. A 33 237

    [17]

    Ellis J W, Bath J 1938 J. Chem. Phys. 6 723

    [18]

    Pegau W S, Gray D, Zaneveld J R V 1997 Appl. Opt. 36 6035

    [19]

    Pope R M, Fry E S 1997 Appl. Opt. 36 8710

    [20]

    Kopelevich O V, Burenkov V I 1977 Oceanology 17 278

    [21]

    Weijer J V D, Gevers T, Gijsenij A 2007 IEEE Trans. Image Process 16 2207

    [22]

    Lee Z, Wei J, Voss K, Lewis M, Bricaud A, Huot Y 2015 Appl. Opt. 54 546

    [23]

    Le M N, Wang G, Zheng H B, Liu J B, Zhou Y, Xu Z 2017 Opt. Express 25 22859

    [24]

    Dubreuil M, Delrot P, Leonard I, Alfalou A, Brosseau C, Dogariu A 2013 Appl. Opt. 52 997

    [25]

    Piederrire Y, Boulvert F, Cariou J, Jeune B L, Guern Y, Brun G L 2005 Opt. Express 13 5030

    [26]

    Li F, Wu J, Wang Y, Zhao Y, Zhang X 2012 IEEE Fifth International Conference on Advanced Computational Intelligence Nanjing, China, March 29-31, 2012 p662

  • [1]

    Lavest J M, Guichard F, Rousseau C 2002 International Conference on Image Processing Rochester, NY, USA, September 22-25, 2002 p813

    [2]

    Panetta K, Gao C, Agaian S 2016 IEEE J. Oceanic Eng. 41 541

    [3]

    Chennu A, Frber P, De'Ath G, de Beer D, Fabricius K E 2017 Sci. Rep. 7 7122

    [4]

    Chiang J Y, Chen Y C 2012 IEEE Trans. Image Process. 21 1756

    [5]

    Zhao X W, Jin T, Chi H, Qu S 2015 Acta Phys. Sin. 64 104201 (in Chinese) [赵欣慰, 金韬, 池灏, 曲嵩 2015 物理学报 64 104201]

    [6]

    Han P L, Liu F, Zhang G, Tao Y, Shao X P 2018 Acta Phys. Sin. 67 054202 (in Chinese) [韩平丽, 刘飞, 张广, 陶禹, 邵晓鹏 2018 物理学报 67 054202]

    [7]

    Liu F, Cao L, Shao X, Han P L, Bin X 2015 Appl. Opt. 54 8116

    [8]

    Huang B J, Liu T G, Han H F, Han J H, Yu M X 2016 Opt. Express 24 9826

    [9]

    Schechner Y Y, Karpel N 2005 IEEE J. Oceanic Eng. 30 570

    [10]

    Han P L, Liu F, Yang K, Ma J Y, Li J J, Shao X P 2017 Appl. Opt. 56 6631

    [11]

    Schechner Y Y, Averbuch Y 2007 IEEE Trans. Pattern Anal. Mach. Intell. 29 1655

    [12]

    Schechner Y Y, Karpel N 2004 IEEE Computer Vision and Pattern Recognition Washington, USA, June 22-25, 2004 p536

    [13]

    Jaffe J S 2010 Opt. Express 18 12328

    [14]

    Guan J G, Zhu J P, Tian H, Hou X 2015 Acta Phys. Sin. 64 224203 (in Chinese) [管今哥, 朱京平, 田恒, 侯洵 2015 物理学报 64 224203]

    [15]

    Treibitz T, Schechner Y Y 2009 IEEE Trans. Pattern Anal. Mach. Intell. 31 385

    [16]

    Liu F, Shao X, Gao Y, Xiang L B, Han P L, Li G 2016 J. Opt. Soc. Am. A 33 237

    [17]

    Ellis J W, Bath J 1938 J. Chem. Phys. 6 723

    [18]

    Pegau W S, Gray D, Zaneveld J R V 1997 Appl. Opt. 36 6035

    [19]

    Pope R M, Fry E S 1997 Appl. Opt. 36 8710

    [20]

    Kopelevich O V, Burenkov V I 1977 Oceanology 17 278

    [21]

    Weijer J V D, Gevers T, Gijsenij A 2007 IEEE Trans. Image Process 16 2207

    [22]

    Lee Z, Wei J, Voss K, Lewis M, Bricaud A, Huot Y 2015 Appl. Opt. 54 546

    [23]

    Le M N, Wang G, Zheng H B, Liu J B, Zhou Y, Xu Z 2017 Opt. Express 25 22859

    [24]

    Dubreuil M, Delrot P, Leonard I, Alfalou A, Brosseau C, Dogariu A 2013 Appl. Opt. 52 997

    [25]

    Piederrire Y, Boulvert F, Cariou J, Jeune B L, Guern Y, Brun G L 2005 Opt. Express 13 5030

    [26]

    Li F, Wu J, Wang Y, Zhao Y, Zhang X 2012 IEEE Fifth International Conference on Advanced Computational Intelligence Nanjing, China, March 29-31, 2012 p662

  • [1] 徐菁焓, 吴国俊, 董晶, 于洋, 封斐, 刘博. 基于Stokes矢量差分法的背景光偏振特性研究. 物理学报, 2023, 72(24): 244201. doi: 10.7498/aps.72.20230639
    [2] 高晨栋, 赵明琳, 卢德贺, 窦健泰. 基于双层多指标优化的水下偏振成像技术. 物理学报, 2023, 72(7): 074202. doi: 10.7498/aps.72.20222017
    [3] 赵富, 胡渝曜, 王鹏, 刘军. 偏振复用散射成像. 物理学报, 2023, 72(15): 154201. doi: 10.7498/aps.72.20230551
    [4] 霍永胜. 基于偏振的暗通道先验去雾. 物理学报, 2022, 71(14): 144202. doi: 10.7498/aps.71.20220332
    [5] 孙雪莹, 刘飞, 段景博, 牛耕田, 邵晓鹏. 基于散斑光场偏振共模抑制性的宽谱散射成像技术. 物理学报, 2021, 70(22): 224203. doi: 10.7498/aps.70.20210703
    [6] 刘飞, 孙少杰, 韩平丽, 赵琳, 邵晓鹏. 基于稀疏低秩特性的水下非均匀光场偏振成像技术研究. 物理学报, 2021, 70(16): 164201. doi: 10.7498/aps.70.20210314
    [7] 冯帅, 常军, 胡瑶瑶, 吴昊, 刘鑫. 偏振成像激光雷达与短波红外复合光学接收系统设计与分析. 物理学报, 2020, 69(24): 244202. doi: 10.7498/aps.69.20200920
    [8] 才啟胜, 黄旻, 韩炜, 丛麟骁, 路向宁. 外差式偏振干涉成像光谱技术研究. 物理学报, 2017, 66(16): 160702. doi: 10.7498/aps.66.160702
    [9] 李克武, 王志斌, 杨常青, 张瑞, 王耀利, 宋雁鹏. 基于声光滤光和液晶相位调谐的高光谱全偏振成像新技术. 物理学报, 2015, 64(14): 140702. doi: 10.7498/aps.64.140702
    [10] 管今哥, 朱京平, 田恒, 侯洵. 基于Stokes矢量的实时偏振差分水下成像研究. 物理学报, 2015, 64(22): 224203. doi: 10.7498/aps.64.224203
    [11] 李成强, 王挺峰, 张合勇, 谢京江, 刘立生, 郭劲. 光源参数及大气湍流对电磁光束传输偏振特性的影响. 物理学报, 2014, 63(10): 104201. doi: 10.7498/aps.63.104201
    [12] 穆廷魁, 张淳民, 李祺伟, 魏宇童, 陈清颖, 贾辰凌. 差分偏振干涉成像光谱仪I.概念原理与操作. 物理学报, 2014, 63(11): 110704. doi: 10.7498/aps.63.110704
    [13] 穆廷魁, 张淳民, 李祺伟, 魏宇童, 陈清颖, 贾辰凌. 差分偏振干涉成像光谱仪Ⅱ.光学设计与分析. 物理学报, 2014, 63(11): 110705. doi: 10.7498/aps.63.110705
    [14] 张斌, 潘雪丰, 陶卫东. 新型内反射旋光光学滤波器研究. 物理学报, 2011, 60(5): 054214. doi: 10.7498/aps.60.054214
    [15] 李山, 钟明亮, 张礼杰, 熊祖洪, 张中月. 偏振方向及结构间耦合作用对空心方形银纳米结构表面等离子体共振的影响. 物理学报, 2011, 60(8): 087806. doi: 10.7498/aps.60.087806
    [16] 张二峰, 戴宏毅. 光的偏振对热光关联成像的影响. 物理学报, 2011, 60(6): 064209. doi: 10.7498/aps.60.064209
    [17] 徐凯, 杨艳芳, 何英, 韩小红, 李春芳. 局域椭圆偏振光束强聚焦性质的研究. 物理学报, 2010, 59(9): 6125-6130. doi: 10.7498/aps.59.6125
    [18] 张 姗, 吴福全, 吴闻迪. 多级石英晶体旋光光学滤波器的滤波特性. 物理学报, 2008, 57(8): 5020-5026. doi: 10.7498/aps.57.5020
    [19] 郑国梁, 佘卫龙. 偏振方向对THz电光探测影响的理论研究. 物理学报, 2006, 55(3): 1061-1067. doi: 10.7498/aps.55.1061
    [20] 周国泉. 任意线偏振高斯光束的非傍轴传输. 物理学报, 2005, 54(10): 4710-4717. doi: 10.7498/aps.54.4710
计量
  • 文章访问数:  6355
  • PDF下载量:  224
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-04-14
  • 修回日期:  2018-05-21
  • 刊出日期:  2019-09-20

/

返回文章
返回