光子学报, 2014, 43 (5): 0530002, 网络出版: 2014-06-03   

高光谱溢油检测中云背景抑制方法研究

Study of Cloud Background Suppression for Oil Spill Detection from Hyperspectral Data
作者单位
西安电子科技大学 物理与光电工程学院,西安 710071
摘要
针对高光谱图像溢油检测过程中云背景的干扰问题,提出一种高光谱场景云背景抑制方法.首先,分析了海面溢油的光谱反射率特性,根据海面溢油中C-H键的光谱特征,介绍了基于伪彩图像的溢油检测方法.其次,比较了高光谱场景中海水、溢油和云背景的辐射特性,依据云背景辐射特性的特点,设计了一种新的云背景辐射光谱特征提取模型,在此基础上,进一步考虑云、海面与溢油的差异,选取云辐射最大的波段图像,结合云背景辐射光谱特征生成云背景抑制图.最后,将云背景抑制图与溢油伪彩图像相乘,得到云背景抑制结果.将本文提出的方法应用于实际墨西哥湾Airborne Visible InfraRed Imaging Spectrometer高光谱遥感影像的海面溢油的检测,结果表明本文提出的方法能够在不影响溢油检测条件下,有效地消除高光谱溢油检测过程中云背景的影响.
Abstract
Hyperspectral sensors can acquire the radiance of a scene in a high resolution both in spatial and spectral dimensions, which produces good benefits for oil spill detection. Because the cloud background in hyperspectral scene severely interfere oil spill detection result, a new method is presented to reduce the cloud background in hyperspectal scenes. Firstly, the spectral reflectance characteristics of oil spill are analyzed. According to the spectral characteristics of the C-H bond of oil spill, the false color generation based oil spill detection method is introduced. Secondly, the radiance characteristics of seawater, oil spill and cloud is compared. Based on the radiation characteristics of cloud, a new model is build to extract the radiance features of cloud. On this basis, the difference of cloud and seawater, and oil spill are considered. And the band image which has maximum cloud radiance is selected. The cloud background suppression map is then generated by using the band image and the radiance feature of the cloud background. Finally, the background suppression result is obtained by multiplying the false color image by background suppression map. The proposed method is applied to the real Airborne Visible InfraRed Imaging Spectrometer hyperspectral image captured during the Deepwater Horizon oil spill in the Gulf of Mexico for oil spill detection. The results show that the proposed method can effectively suppress the cloud background for oil spill detection from hyperspectral data, and does not affect the oil spill detection performance.
参考文献

[1] BREKKEA C, SOLBERG A H S. Oil spill detection by satellite remote sensing[J]. Remote Sensing of Environment, 2005, 95(1):1-13.

[2] SOLBERG A H S, STORVIK G, SOLBERG R et al. Automatic detection of oil spills in ERS SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(4): 1916-1924.

[3] SHEN S S, LEWIS P E. Deepwater horizon oil spill monitoring using airborne multispectral infrared imagery[C]. SPIE, 2011, 8048: 80480H-1.

[4] LEIFER I, LEHR W J, SIMECEK-BEATTY D, et al. State of the art satellite and airborne marine oil spill remote sensing: application to the BP Deepwater Horizon oil spill[J]. Remote Sensing of Environment, 2012, 124(9): 185-209.

[5] JHA M N, LEVY J, CAO Y. Advances in remote sensing for oil spill disaster management: state-of-the-art sensors technology for oil spill surveillance[J]. Sensor, 2008, 8(1): 236-255.

[6] LENNON M, BABICHENKO S, THOMAS N, et al. Detection and mapping of oil slicks in the sea by combined use of hyperspectral imagery and laser-induced fluorescence[C]. EARSeLe Proceedings, 2006, 5(1): 120-128.

[7] SALEM F, KAFATOS M, EL-GHAZAWI T, et al. Hyperspectral image assessment of oil-contaminated wetland [J]. International Journal of Remote Sensing, 2005, 26(4): 811-821.

[8] HU C, LI X, PICHEL W G, et al. Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery[J]. Geophysical Research Letters, 2009, 36(1): L01604.

[9] KOKALY R F, HOEFEN T M, LIVO K E, et al. A rapid method for creating qualitative images indicative of thick oil emulsion on the ocean's surface from imaging spectrometer data[R]. U.S. Geological Survey Open-File Report 2010-1107, 2010:1-9.

[10] CLARK R N, SWAYZE G A, LEIFER I, et al. A method for qualitative mapping of thick oil spills using imaging spectroscopy[R]. U.S. Geological Survey Open-File Report 2010-1101, 2010: 1-4.

[11] 李颖,刘丙新,李宝玉,等. 基于小波变换的油膜光谱特征分析[J]. 光谱学与光谱分析, 2012, 32(7):1923-1927.

    LI Ying, LIU Bing-xin, LI Bao-yu, et al. Analysis of spectral characteristics of oil film on water based on wavelet transform[J]. Spectroscopy and Spectral Analysis, 2012, 32(7): 1923-1927.

[12] 陆应诚, 田庆久, 齐小平等. 海面甚薄油膜光谱响应研究与分析[J]. 光谱学与光谱分析, 2009, 29(4):986-989.

    LU Ying-cheng, TIAN Qing- jiu, QI Xiao- ping, et al. Spectral response analysis of offshore thin oil slicks[J]. Spectroscopy and Spectral Analysis, 2009, 29(4): 986-989.

[13] 童庆禧, 张兵, 郑兰芬. 高光谱遙感的多学科应用[M]. 北京: 电子工业出版社, 2006.

[14] 黄敏, 朱晓, 朱启兵,等. 基于高光谱图像的玉米种子特征提取与识别[J].光子学报, 2012, 41(7):868-873.

    HUANG Min, ZHU Xiao, ZHU Qi-bing, et al. Morphological characteristics of maize seed extraction and identification based on the hyperspectral image[J]. Acta Photonica Sinica, 2012, 41(7): 868-873.

[15] 王跃明, 祝倩, 王建宇,等. 短波红外高光谱成像仪背景辐射特征研究. 红外与毫米波学报, 2011, 30(3):279-283.

    WANG Yue-ming, ZHU Qian, WANG Jian-yu et al. Characterization of background radiation in SWIR hyperspectral imager[J]. Joural of Infrared and Millimeter Waves, 2011, 30(3): 279-283.

刘德连, 李昭慧, 张建奇. 高光谱溢油检测中云背景抑制方法研究[J]. 光子学报, 2014, 43(5): 0530002. LIU De-lian, LI ZHAO-hui, ZHANG Jian-qi. Study of Cloud Background Suppression for Oil Spill Detection from Hyperspectral Data[J]. ACTA PHOTONICA SINICA, 2014, 43(5): 0530002.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!