海洋图像智能信息提取方法研究
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摘要
随着科学和技术的发展,人类与海洋的关系越来越密切,海洋向人类提供生存和发展必不可少的物质和能源,还对地球气候与生态变化有重要影响。海洋环境监测与海洋资源探测研究的不断深入发展都需要海洋信息作为基础,使海洋信息技术成为近年来快速发展的新兴领域。长期以来海洋卫星遥感技术为环境监测与调查积累了海量、动态、多源、多维的海洋环境数据,然而由于海洋图像信息提取技术的相对滞后,大量宝贵数据资源得不到充分利用,造成数据丰富而知识贫乏的状况,因而进行从海洋图像中提取信息的理论和技术的研究是进一步开发海洋、保护海洋的关键。
智能信息提取是应用计算智能、知识发现、机器学习等方法实现领域数据的智能化信息处理,它是为从大量的复杂的多样数据集中提取隐含的潜在有用的知识而进行的探索性数据资料分析,近20年来在理论研究和技术应用方面都得到了丰富的发展,为人类认识世界提供了强有力的工具。
本论文以海洋图像信息提取为研究目标,将智能方法和图像信息、海洋卫星遥感相结合,对抽象的海洋卫星图像信息层次模型和具体的海洋卫星图像信息智能提取技术都进行了探索,搭建了基于网络的海洋卫星图像信息管理、提取、共享平台,主要研究内容和创新点如下：
1.应用创新：基于流形学习的海洋温度场图像分析。把流形学习应用到海洋环境场图像分析中,将海洋温度场数据以高维度拓扑流形的角度进行观察,从高维海洋温度场采样数据中以非线性降维的方式恢复低维流形结构,即找到高维空间中的低维流形,并求出相应的嵌入映射,研究内嵌空间维度变化和海表面温度场数据集时空范围间的关系,分析低维维度的海洋学意义,讨论低维投影分布的特点和异常点的应用。实验证明海洋温度场的非线性低维映射可以保存温度场分布的信息,和主成分分析方法相比具有更快的收敛速度和表达非线性信息准确的优势,并发现低维投影异常距离和厄尔尼诺指数间存在正向的对应关系,具有应用于厄尔尼诺判定的价值,流形学习提供了一个海洋图像信息提取的新角度。
2.方法创新：基于核方法的海洋中尺度涡旋识别算法研究。研究基于监督学习的海洋中尺度涡旋识别算法,引入核方法作为判断涡旋相似性的度量,设计结构统计核函数(SSF, Structral Statistical Function)来预测涡旋中心位置,并设计图像滑动窗口算法提取海洋流场图像中的多个涡旋,测试结果显示本方法涡旋识别正确率为97.6%,与流场矢量约束算法相比具有更高的涡旋识别灵敏度。结合海洋学知识(中尺度涡旋的流场特征和海平面高度特征)进行图像涡旋预选,并以并行运算技术提高涡旋分类速度,提高方法运行效率。
3.技术创新：面向网络的自动化海洋卫星图像信息平台设计与开发。分析了网络环境下海洋卫星图像信息集成的模式和实现技术,提出一个自动化运行的海洋卫图像网络集成信息平台体系结构,根据业务流程建模理论和基于SOA的分布式系统理论,设计并实现了一个分布式的海洋卫星图像信息网络集成平台,可在网络上自动地完成数据处理、时空分析和可视化等功能的信息服务,已在多个项口中得到成功应用。
研究结果表明,本文设计的海洋卫星图像智能信息提取模型能够合理的从整体和局部提取数据中蕴含的知识,进行的信息提取研究发现了海洋温度场低维嵌入空间的知识并以监督方法探测出海洋中尺度涡旋的时空分布等特征；设计开发的海洋卫星图像信息平台能够在网络环境下提供高效稳定的信息服务。
Along with the development of science and technology, the relationship between human and marine has become more and more closely. Marine not only provides necessary material and energy for human beings to support the survival and development, but also plays an important role in climate change and ecology. The research of marine environmental monitoring and marine resources exploration need marine information to serve as a foundation, and the marine information technology has become a new developing field in recent years. For several decades, marine satellite remote sensing technology has accumulated massive, dynamic, multi source and multidimensional marine environmental data for marine monitoring and investigation, however, the research of information extraction technology is lagging behind data acquisition, valuable data resources potential can not be fully developed and utilized, and people are now facing the problem of "rich data and poor knowledge". The theory and technology study of information from marine satellite images is one key to exploit and protect marine.
Intelligent information extraction is to apply computational intelligence methods such as: knowledge discovery, machine learning, to process domain data. It is a kind of explorative data analysis to discover previously unknown and potentially useful knowledge from massive, complicated and diversified dataset. In the past twenty years, its theory research and technical application have been increasingly enriched and it has provided human a powerful tool to know the world.
This dissertation takes marine satellite image information intelligent extraction as the research object, it combines computational intelligence methods, image information structure and marine satellite remote sensing together. An abstract marine satellite image information model has been introduced and concrete intelligent methods have been studied, finally a web based marine satellite image information platform has been designed and implemented. The main contents and innovations are summarized as follows.
1. Application Innovation:Manifold learning based sea surface temperature image analysis. Nonlinear dimension reduction is employed to get the low dimensional manifold structure from high dimensional sea surface temperature images, that is, to find the embedded projection. The dissertation discusses the relation between intrinsic space dimensionality and space time range. With the help of dimension meaning, the characteristics of low dimensional space such as projection distribution, anomaly point, have been researched. The result of experiment shows that the exception distance corresponds to ONI index and it has certain ability to judge El Nino phenomenon.
2. Procedure Innovation:Kernel method based marine mesoscale eddies recognition. In this dissertation, kernel method is employed to measure the similarity of eddies, and a structural statistical function is described to predict the location of eddy center. Sliding window algorithm is proposed to detect multiple eddies in one sea current image. Oceanography knowledge (feature of mesoscale eddy) and SSE technique is adopted to accelerate the speed of eddy classification. The experiment shows that this method can get higher accuracy (97.6%) of eddy recognition than current vector constraint algorithm.
3. Technology Innovation:Design and implementation of web based operational marine satellite image information platform. After analyzing the pattern of marine satellite image information (original and product) management and sharing in web environment, an operational workflow of marine scientific research is built. Service-Oriented Architecture (SOA) is taken to design and implement a web-based distributed marine satellite information platform. The platform has already been used in several projects.
The research result indicates that the abstract marine satellite image information extraction model of this dissertation can discover oceanography knowledge from different perspectives. The field based image analysis retrieves low dimensional special knowledge of sea surface temperature field and the object based method analyzes the distribution feature of mesoscale eddies through supervised algorithm. The marine satellite information platform can provide user centered information service under a network environment.
智能信息提取是应用计算智能、知识发现、机器学习等方法实现领域数据的智能化信息处理,它是为从大量的复杂的多样数据集中提取隐含的潜在有用的知识而进行的探索性数据资料分析,近20年来在理论研究和技术应用方面都得到了丰富的发展,为人类认识世界提供了强有力的工具。
本论文以海洋图像信息提取为研究目标,将智能方法和图像信息、海洋卫星遥感相结合,对抽象的海洋卫星图像信息层次模型和具体的海洋卫星图像信息智能提取技术都进行了探索,搭建了基于网络的海洋卫星图像信息管理、提取、共享平台,主要研究内容和创新点如下：
1.应用创新：基于流形学习的海洋温度场图像分析。把流形学习应用到海洋环境场图像分析中,将海洋温度场数据以高维度拓扑流形的角度进行观察,从高维海洋温度场采样数据中以非线性降维的方式恢复低维流形结构,即找到高维空间中的低维流形,并求出相应的嵌入映射,研究内嵌空间维度变化和海表面温度场数据集时空范围间的关系,分析低维维度的海洋学意义,讨论低维投影分布的特点和异常点的应用。实验证明海洋温度场的非线性低维映射可以保存温度场分布的信息,和主成分分析方法相比具有更快的收敛速度和表达非线性信息准确的优势,并发现低维投影异常距离和厄尔尼诺指数间存在正向的对应关系,具有应用于厄尔尼诺判定的价值,流形学习提供了一个海洋图像信息提取的新角度。
2.方法创新：基于核方法的海洋中尺度涡旋识别算法研究。研究基于监督学习的海洋中尺度涡旋识别算法,引入核方法作为判断涡旋相似性的度量,设计结构统计核函数(SSF, Structral Statistical Function)来预测涡旋中心位置,并设计图像滑动窗口算法提取海洋流场图像中的多个涡旋,测试结果显示本方法涡旋识别正确率为97.6%,与流场矢量约束算法相比具有更高的涡旋识别灵敏度。结合海洋学知识(中尺度涡旋的流场特征和海平面高度特征)进行图像涡旋预选,并以并行运算技术提高涡旋分类速度,提高方法运行效率。
3.技术创新：面向网络的自动化海洋卫星图像信息平台设计与开发。分析了网络环境下海洋卫星图像信息集成的模式和实现技术,提出一个自动化运行的海洋卫图像网络集成信息平台体系结构,根据业务流程建模理论和基于SOA的分布式系统理论,设计并实现了一个分布式的海洋卫星图像信息网络集成平台,可在网络上自动地完成数据处理、时空分析和可视化等功能的信息服务,已在多个项口中得到成功应用。
研究结果表明,本文设计的海洋卫星图像智能信息提取模型能够合理的从整体和局部提取数据中蕴含的知识,进行的信息提取研究发现了海洋温度场低维嵌入空间的知识并以监督方法探测出海洋中尺度涡旋的时空分布等特征；设计开发的海洋卫星图像信息平台能够在网络环境下提供高效稳定的信息服务。
Along with the development of science and technology, the relationship between human and marine has become more and more closely. Marine not only provides necessary material and energy for human beings to support the survival and development, but also plays an important role in climate change and ecology. The research of marine environmental monitoring and marine resources exploration need marine information to serve as a foundation, and the marine information technology has become a new developing field in recent years. For several decades, marine satellite remote sensing technology has accumulated massive, dynamic, multi source and multidimensional marine environmental data for marine monitoring and investigation, however, the research of information extraction technology is lagging behind data acquisition, valuable data resources potential can not be fully developed and utilized, and people are now facing the problem of "rich data and poor knowledge". The theory and technology study of information from marine satellite images is one key to exploit and protect marine.
Intelligent information extraction is to apply computational intelligence methods such as: knowledge discovery, machine learning, to process domain data. It is a kind of explorative data analysis to discover previously unknown and potentially useful knowledge from massive, complicated and diversified dataset. In the past twenty years, its theory research and technical application have been increasingly enriched and it has provided human a powerful tool to know the world.
This dissertation takes marine satellite image information intelligent extraction as the research object, it combines computational intelligence methods, image information structure and marine satellite remote sensing together. An abstract marine satellite image information model has been introduced and concrete intelligent methods have been studied, finally a web based marine satellite image information platform has been designed and implemented. The main contents and innovations are summarized as follows.
1. Application Innovation:Manifold learning based sea surface temperature image analysis. Nonlinear dimension reduction is employed to get the low dimensional manifold structure from high dimensional sea surface temperature images, that is, to find the embedded projection. The dissertation discusses the relation between intrinsic space dimensionality and space time range. With the help of dimension meaning, the characteristics of low dimensional space such as projection distribution, anomaly point, have been researched. The result of experiment shows that the exception distance corresponds to ONI index and it has certain ability to judge El Nino phenomenon.
2. Procedure Innovation:Kernel method based marine mesoscale eddies recognition. In this dissertation, kernel method is employed to measure the similarity of eddies, and a structural statistical function is described to predict the location of eddy center. Sliding window algorithm is proposed to detect multiple eddies in one sea current image. Oceanography knowledge (feature of mesoscale eddy) and SSE technique is adopted to accelerate the speed of eddy classification. The experiment shows that this method can get higher accuracy (97.6%) of eddy recognition than current vector constraint algorithm.
3. Technology Innovation:Design and implementation of web based operational marine satellite image information platform. After analyzing the pattern of marine satellite image information (original and product) management and sharing in web environment, an operational workflow of marine scientific research is built. Service-Oriented Architecture (SOA) is taken to design and implement a web-based distributed marine satellite information platform. The platform has already been used in several projects.
The research result indicates that the abstract marine satellite image information extraction model of this dissertation can discover oceanography knowledge from different perspectives. The field based image analysis retrieves low dimensional special knowledge of sea surface temperature field and the object based method analyzes the distribution feature of mesoscale eddies through supervised algorithm. The marine satellite information platform can provide user centered information service under a network environment.
引文
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