冰区溢油雷达监测技术研究
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摘要
随着对海洋全球性地开发以及近年来频繁的海冰灾害,冰区溢油的防治已经引起了全球的关注。在我国,渤海海域每年冬季发生的海冰灾害对该海域的海上石油工程、船舶运输、沿岸人民群众的生活以及该海域的环境都带来了不同程度的影响。它不仅能够封冻港口、堵塞航道、中断交通运输,而且还能破坏港工设施,撞毁海上过往船只及海上结构物。海冰灾害同样加大了发生冰区溢油事故的可能,而冰区溢油的防治比开阔海域溢油的防治更加困难。因此,开展冰区溢油的监测及漂移动态预报工作,对于保护海洋环境和保障航运安全都具有重要的现实意义。
本论文主要通过对航海雷达采集的冰区溢油海面图像的一系列分析和处理,获取海冰及溢油的相关信息,从而实现对冰区溢油的远距离监测。通过采用小波变换建立低通滤波器去除原始图像中的有害噪声,再通过计算机编程技术对图像作分类处理,从而获取海冰及溢油的面积、分布状况、漂移速度与方向等重要参数,为冰区溢油的实时监测及进一步的漂移动态预报工作提供技术支持。主要的工作如下：
(1)对采集的雷达图像作三层小波变换,去除原始图像中的噪声。同时也采用中值滤波方法对原始图像作滤波处理,二者比较发现,小波变换去噪效果更佳,对于后续的处理与分析更为有利。
(2)应用图像处理技术,根据海冰雷达指纹库和油膜雷达指纹库数据,获取海冰及溢油的的分布状况,并分析每种海冰在一定时间间隔内分布状况的变化。
(3)通过编制程序,分析计算每种海冰及油膜的面积、相对于监测位置的最远及最近的距离以及平均漂移速度及方向等重要数据,为冰区溢油的实时监测及进一步的漂移动态预报工作提供技术支持。
(4)用VC语言设计实现程序执行及数据显示界面,使操作更加直观、便捷。
With the global exploitation to the ocean and frequent sea ice disaster, the whole world has paid attention to oil spill of ice region. In China, ice condition occurs every winter in Bohai, which influents marine petroleum engineering, marine transport, people's life and the environment. Not only can it freeze the port, block the sea channel, break off the transportation, it also can destroy the port installations and crash out ships. Sea ice also increased the occurrence of oil spill of ice region. And ince oil spill prevention is much more difficult. Hence, in order to protect the marine environment and ensure the safety of maritime security in ice area, monitoring oil spill of ice region an forecasting drifting dynamically have realistic significance.
My research picked ice oil spill radar images with a marine radar, processed and analyzed the original images and acquired important information about sea ice and oil, to remote monitor ice oil spill. Adopt wavelet transform to build a low-pass filter, and then it can decrease noise in original images. Classify images by using computer programming technology to acquire acreage, distribution, drift speed and direction of sea ice and oil. These information can provide technology support to monitoring and forecasting oil spill of ice region. The dones following:
1. Make triple wavelet transform to the original images, and then decrease the noise. Adopt median filtering to same images and compare the effect. The result is that de-noising through wavelet transform is better.
2. Through image processing technology, according to Sea ice radar fingerprint database and oil film radar fingerprint database classify sea ice and oil film. Analyze their changing situation.
3. Analyze distribution, acreage, max and closest distance from the platform, drift speed of sea ice and oil film, provide technology support to monitoring and forecasting oil spill of ice region
4. By using Visual C++, design the program interface to make operation more convenient.
本论文主要通过对航海雷达采集的冰区溢油海面图像的一系列分析和处理,获取海冰及溢油的相关信息,从而实现对冰区溢油的远距离监测。通过采用小波变换建立低通滤波器去除原始图像中的有害噪声,再通过计算机编程技术对图像作分类处理,从而获取海冰及溢油的面积、分布状况、漂移速度与方向等重要参数,为冰区溢油的实时监测及进一步的漂移动态预报工作提供技术支持。主要的工作如下：
(1)对采集的雷达图像作三层小波变换,去除原始图像中的噪声。同时也采用中值滤波方法对原始图像作滤波处理,二者比较发现,小波变换去噪效果更佳,对于后续的处理与分析更为有利。
(2)应用图像处理技术,根据海冰雷达指纹库和油膜雷达指纹库数据,获取海冰及溢油的的分布状况,并分析每种海冰在一定时间间隔内分布状况的变化。
(3)通过编制程序,分析计算每种海冰及油膜的面积、相对于监测位置的最远及最近的距离以及平均漂移速度及方向等重要数据,为冰区溢油的实时监测及进一步的漂移动态预报工作提供技术支持。
(4)用VC语言设计实现程序执行及数据显示界面,使操作更加直观、便捷。
With the global exploitation to the ocean and frequent sea ice disaster, the whole world has paid attention to oil spill of ice region. In China, ice condition occurs every winter in Bohai, which influents marine petroleum engineering, marine transport, people's life and the environment. Not only can it freeze the port, block the sea channel, break off the transportation, it also can destroy the port installations and crash out ships. Sea ice also increased the occurrence of oil spill of ice region. And ince oil spill prevention is much more difficult. Hence, in order to protect the marine environment and ensure the safety of maritime security in ice area, monitoring oil spill of ice region an forecasting drifting dynamically have realistic significance.
My research picked ice oil spill radar images with a marine radar, processed and analyzed the original images and acquired important information about sea ice and oil, to remote monitor ice oil spill. Adopt wavelet transform to build a low-pass filter, and then it can decrease noise in original images. Classify images by using computer programming technology to acquire acreage, distribution, drift speed and direction of sea ice and oil. These information can provide technology support to monitoring and forecasting oil spill of ice region. The dones following:
1. Make triple wavelet transform to the original images, and then decrease the noise. Adopt median filtering to same images and compare the effect. The result is that de-noising through wavelet transform is better.
2. Through image processing technology, according to Sea ice radar fingerprint database and oil film radar fingerprint database classify sea ice and oil film. Analyze their changing situation.
3. Analyze distribution, acreage, max and closest distance from the platform, drift speed of sea ice and oil film, provide technology support to monitoring and forecasting oil spill of ice region
4. By using Visual C++, design the program interface to make operation more convenient.
引文
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[2]李志军.中国海洋平台.2000,15(5)：20.
[3]吴龙涛,吴辉碇,李万彪等.渤海冰漂移对海面风场、潮流场的响应.海洋学报.2005,27(5)： 16-21.
[4]曲俊生.海冰数值模拟预报：(硕士学位论文).大连：大连海事大学,2009.
[5]孙延维,董须瑜,张立锟等.雷达观测海冰分类的研究.海洋学报.1992,14(1)：115-123.
[6]潘德炉,李炎.海洋光学遥感技术的发展和前沿.中国工程科学.2003,5(3)：39-43.
[7]赵宝刚.渤海辽东湾冰区工程点雷达海冰监测和预报技术研究[D]：(博士学位论文).大连：大连海事大学环境科学与工程学院,2008.
[8]刘钦政,白珊,吴辉碇.中国海冰研究[J].海洋预报.1998,15(4)：8-13.
[9]BAI Shan. Sea ice disaster in 1969[C].//Proceeding Of International Conference on Marine Disaster:Forecast and Reduction. Beijing:China Ocean Press.1988: 115-122.
[10]WU Huiding, BAI Shan, LI Hai, et al. Sea ice Monitoring and Forecasting in China [C].//Proceeding of Workshop on Mapping and Archiving of Sea Ice Data-the Expanding Role of Radar. Ottawa, Canada:WMO/TD-NO.2000,1027:65-72.
[11]HUANG Runheng, WANG Qiang, JIN Zhengang. Application of Satellite Imagery to Monitoring of Sea ice Motion in Northern China Seas[J]. Advanced Space Research. 1992,12 (7):163-167.
[12]WU Huiding, BAI Shan, ZHANG Zhanhai. Numerical sea ice prediction in China[J]. Acta Oceanologica Sinica.1998,17 (2):167-185.
[13]WU Huiding, BAI Shan, LI Hai, et al. Modeling and Forecasting of Bohai Sea ice[J] of Cold Region Engineering,2000,14 (2):68-80.
[14]LUO Yawei, WU Huiding, ZHANG Yunfei, et al. Application if HY-1 Satellite to sea ice Monitoring and Forecasting[J]. Acta Oceanologica Siniea.2004,23 (2): 251-266.
[15]Lew Iseo, Curriebw, Haykins. Detection and Classification of Ice[M]. Letchworth: Research Studies Press.1987.
[16]孙延维,董须瑜,张立锟等.雷达测冰试验初报[J].海洋科学.1983,1：50-52.
[17]Aeberl Fml, Manorem. Mapping of sea ice and measuring of its drift using aircraft synthetic aperture radar images[J]. J Geophys Res.1984,84:1827-1835.
[18]David JL, Dennis MN. The role of RADAR SAT within the context of an operational ice information system[A]. Sea Ice Observation and Moedeling[C]. Beijing:China Ocean Press.1994,274-285.
[19]Kova SA, Morey RM. Airborne sea ice thickness electro magnetic sounding if sea ice thickness[J]. Cold Reg Sci Technol.1989,14:239-311.
[20]靳济芳.Visual C++小波变换技术与工程实践.北京：人民邮电出版社.2001.
[21]张海建.基于小波去噪预处理的图像模糊边缘检测研究：(硕十学位论文).成都：西南交通大学,2008.
[22]Rioul 0. and Vetterli M. Wavelets and signal Processing. IEEE Signal Processing Magazine,1991,10,8 (4):14-38.
[23]张德丰.Matlab小波分析与工程应用.北京：国防工：业出版社.2008.
[24]成礼智,郭汉伟.小波与离散变换理论及工程实践.北京：清华大学出版社.2005.
[25]杨娜.基于小波变换的雷达图像处理：(硕士学位论文).大连：大连海事大学,2009.
[26]邓东皋,彭立中.小波分析.数学进展.1991,20(3)：294-310.
[27]刘贵忠,邸双亮.小波分析及其应用.西安：西安电子科技大学出版社.1993.
[28]陈武凡.小波分析及其在图像处理中的应用[M].北京：科学出版社.2002.
[29]Mallat S G. A theory of multiresolution signal decomposition:the wavelet representation IEEE Trans on PAMI.1989,11 (7):674-693.
[30]陈贺新.非线性滤波器与数字图像处理.北京：国防工业出版社.2005.
[31]Cohen A. Wavelets and multiscale signal processing. Chapman and Hall.1995.
[32]Chui, C.K. An introduction to wavelets. Academic Press.2002.
[33]Danbechies I. Ten lectures on wavelets. SLAM.2002.
[34]Antoniadis, Pham DT[J]. Wavelets regression for random or irregular design. Comp. Stat. and Data Analysis.2004.
[35]曾诚.基于小波理论的图像去噪和增强技术研究：(硕十学位论文).武汉：武汉理工大学,2008.
[36]王计生,喻俊馨.基于傅立叶变换和小波变换的信号处理.四川工业学报.2003：47-49.
[37]毕为民,唐炬,姚陈果.基于熵阈值的小波包变换抑制局部放电窄带干扰的研究.中国电机工程学报.2003：23(5)：128-131.
[38]Unser M. Texture classification and segmentation using wavelet frames. IEEE Trans. on IP.1995:4 (11):1549-1560.
[39]王玲.多小波理论及其在图像处理中的应用研究.西安：西安电子科技大学.2000.
[40]杨建国.小波分析及其应用[M].北京：机械工：业出版社.2005.
[41]徐晨,赵瑞珍,甘小冰.小波分析应用算法[M].北京：科学出版社.2004.
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