面向目标的信息提取方法研究
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摘要
遥感信息提取是遥感图像处理研究领域中的一项主要内容,也是模式分类范畴研究的课题。遥感图像信息提取的精度直接影响遥感数据的应用水平,高分辨率遥感图像中蕴含丰富信息,是很好信息源。论文以QuickBird(“快鸟”)卫星遥感影像为基础数据,进行一系列信息提取研究,探索信息提取技术和具体方法流程。
研究以图形工作站作为研究平台,使用多种遥感图像处理软件对目标信息(黄河马尔挡地区的有林地信息、水体系信息和交通要素信息等)进行提取,并根据实地调研数据进行精度验证与评价,为信息的准确提取提供依据。本文的研究内容主要工作包括:
(1)完成了多源空间数据集成,为GIS决策分析提供了数据支撑。针对GIS中存在的空间数据多源化问题,采用数据格式转换法实现了空间数据集成。通过利用该方法实现了研究区各类空间数据的融合集成,为GIS空间决策分析提供了数据基础。
(2)依据国内外关于信息提取的基本方法,通过对遥感影像进行预处理,通过做图像增强、图像配准、数据融合,采用监督(或非监督)分类等一系列的处理工作进行了图像有用信息的提取。
(3)完成了基于ERDAS Imagine、PCI和ENVI的遥感和数据图像处理技术,以黄河马尔挡地区遥感影像数据为数据源,对水系、有林地和交通信息等的非监督分类进行了探索,并将分类结果进行比较,并给出最佳提取方法的结论。
(4)以不同的提取信息作为目标对象,在ERDAS Imagine、ENVI和PCI软件上,通过采用不同的算法进行信息提取。得出了针对不同提取对象,适合的软件和提取方法的结论,分别以时间和空间精度为指标对研究结果进行了评价。
(5)其他分类方法的研究与实现。
黄河马尔挡地区多源遥感信息提取的研究已用于实践,结果表明,本论文所提出的各方法具有现实的指导意义,能够完成许多常规手段无法完成的工作,大大节约人力、财力和物力,提高工作效率,为工程决策提供强大的技术支持。信息提取流程取得了一定程度的效果。通过论文中对一些方法的对比分析可以发现,不同的信息提取方法适用于不同的对象的信息提取,需要根据实际所需的信息类型选择合适的方法进行操作。
Remote sensing images information extraction is a major content in the remote sensing images research field, and it is also the subject of the study in the pattern classification. Remote sensing images, and the accuracy of information obtained directly affect the application of remote sensing data and its practical value. High-resolution remote sensing images possess a wealth of information, which are the rich resources of needed information. This paper use the most recently applied quickbird (" QuickBird") remote sensing images as the basic data. With the help of those data, according to the information extracted technical methods and processes, a series of researchs on the information extraction have been carried out. Therefore, the author put forward information extraction techniques and specific methods and processes.
This study uses the graphics workstation as a research platform, and takes various remote sensing images processors to extract the targeted information (the YellowRiver in the area of Merdang Wood land information, the water system and the information of traffic elements ) . Meanwhile, the precise verification and evaluation are based on the spot investigated and surveyed data, which are the basis of the precise extraction of information. The major researching contents and methods of this paper include :
(1) Done on the integration of the space data of multiple sources and gave the data support to the GIS policy analysis. Aimed at solving the problem of mediamatrix of space data in GIS, used the data format integration to accomplish the space data integration. By using this method to achieve the amalgamation and integration of various space data in the researching area, and provided a data basis of the space policy-making and analysis in GIS.
(2) Based on the basic methods of remote sensing images from domestic and overseas, therefore, extracted the useful images according to a series of processing processduers, such as enhancing the images, registering the images, amalgamating the data, and superving classfication (u nsupervising classfication) .
(3)Accomplished the images’remoting and processing technique based on the ERDAS, PCI and ERDAS Imagine. Based on the remoting images data of the Yellow River in the area of Merdang Wood land as the data source, explored the unsupervising classfication of the water system and the information of traffic elements,and so on.In addition, compared with the classfied results to work out the conclusion of the best integration method.
(4)In the ERDAS Imagine, ENVI and PCI softwares, used the different extracting informations as target subjects to extract informations according to the different algorithms.It turned out that different extracting subjects, should ues the suitable softwares and extracting methods.It evaluated the research results form the accuracy of the time and the space.
(5)Other categories of study and implementation.
The multiple sources remote sensing information extraction of the Yellow River in the area of Merdang Wood land has been already applied to the practice.It turned out that the various methods put forward in this paper have realistic directing functions, can complete plenty of unusual works which can’t be done by the regular methods, save the man power, financial investments, and materials, improve the rate working efficiency, and give a strong technique support to the project decisions.The process of extracting the informations has been improved from certain degrees.According to the comparison and analysis on those methods in this paper, the author has found out that different information extraction methods are applied to differet subjects, and we should choose the suitable methods to carry out according to the practical types of the needing informations.
研究以图形工作站作为研究平台,使用多种遥感图像处理软件对目标信息(黄河马尔挡地区的有林地信息、水体系信息和交通要素信息等)进行提取,并根据实地调研数据进行精度验证与评价,为信息的准确提取提供依据。本文的研究内容主要工作包括:
(1)完成了多源空间数据集成,为GIS决策分析提供了数据支撑。针对GIS中存在的空间数据多源化问题,采用数据格式转换法实现了空间数据集成。通过利用该方法实现了研究区各类空间数据的融合集成,为GIS空间决策分析提供了数据基础。
(2)依据国内外关于信息提取的基本方法,通过对遥感影像进行预处理,通过做图像增强、图像配准、数据融合,采用监督(或非监督)分类等一系列的处理工作进行了图像有用信息的提取。
(3)完成了基于ERDAS Imagine、PCI和ENVI的遥感和数据图像处理技术,以黄河马尔挡地区遥感影像数据为数据源,对水系、有林地和交通信息等的非监督分类进行了探索,并将分类结果进行比较,并给出最佳提取方法的结论。
(4)以不同的提取信息作为目标对象,在ERDAS Imagine、ENVI和PCI软件上,通过采用不同的算法进行信息提取。得出了针对不同提取对象,适合的软件和提取方法的结论,分别以时间和空间精度为指标对研究结果进行了评价。
(5)其他分类方法的研究与实现。
黄河马尔挡地区多源遥感信息提取的研究已用于实践,结果表明,本论文所提出的各方法具有现实的指导意义,能够完成许多常规手段无法完成的工作,大大节约人力、财力和物力,提高工作效率,为工程决策提供强大的技术支持。信息提取流程取得了一定程度的效果。通过论文中对一些方法的对比分析可以发现,不同的信息提取方法适用于不同的对象的信息提取,需要根据实际所需的信息类型选择合适的方法进行操作。
Remote sensing images information extraction is a major content in the remote sensing images research field, and it is also the subject of the study in the pattern classification. Remote sensing images, and the accuracy of information obtained directly affect the application of remote sensing data and its practical value. High-resolution remote sensing images possess a wealth of information, which are the rich resources of needed information. This paper use the most recently applied quickbird (" QuickBird") remote sensing images as the basic data. With the help of those data, according to the information extracted technical methods and processes, a series of researchs on the information extraction have been carried out. Therefore, the author put forward information extraction techniques and specific methods and processes.
This study uses the graphics workstation as a research platform, and takes various remote sensing images processors to extract the targeted information (the YellowRiver in the area of Merdang Wood land information, the water system and the information of traffic elements ) . Meanwhile, the precise verification and evaluation are based on the spot investigated and surveyed data, which are the basis of the precise extraction of information. The major researching contents and methods of this paper include :
(1) Done on the integration of the space data of multiple sources and gave the data support to the GIS policy analysis. Aimed at solving the problem of mediamatrix of space data in GIS, used the data format integration to accomplish the space data integration. By using this method to achieve the amalgamation and integration of various space data in the researching area, and provided a data basis of the space policy-making and analysis in GIS.
(2) Based on the basic methods of remote sensing images from domestic and overseas, therefore, extracted the useful images according to a series of processing processduers, such as enhancing the images, registering the images, amalgamating the data, and superving classfication (u nsupervising classfication) .
(3)Accomplished the images’remoting and processing technique based on the ERDAS, PCI and ERDAS Imagine. Based on the remoting images data of the Yellow River in the area of Merdang Wood land as the data source, explored the unsupervising classfication of the water system and the information of traffic elements,and so on.In addition, compared with the classfied results to work out the conclusion of the best integration method.
(4)In the ERDAS Imagine, ENVI and PCI softwares, used the different extracting informations as target subjects to extract informations according to the different algorithms.It turned out that different extracting subjects, should ues the suitable softwares and extracting methods.It evaluated the research results form the accuracy of the time and the space.
(5)Other categories of study and implementation.
The multiple sources remote sensing information extraction of the Yellow River in the area of Merdang Wood land has been already applied to the practice.It turned out that the various methods put forward in this paper have realistic directing functions, can complete plenty of unusual works which can’t be done by the regular methods, save the man power, financial investments, and materials, improve the rate working efficiency, and give a strong technique support to the project decisions.The process of extracting the informations has been improved from certain degrees.According to the comparison and analysis on those methods in this paper, the author has found out that different information extraction methods are applied to differet subjects, and we should choose the suitable methods to carry out according to the practical types of the needing informations.
引文
[1]赵文吉,胡卓玮,李家存,赵秀怡.PCI图像处理教程[M].中国环境科学出版社. 2007.
[2]李小娟,宫兆宁,刘晓萌,李静等编译. ENVI遥感影像处理教程[M].中国环境科学出版社. 2007.
[3]赵文吉,段福州,刘晓萌,徐智勇等编译. ENVI遥感影像处理专题与实践[M].中国环境科学出版社. 2007.
[4]党安荣,王晓栋,陈晓峰,张建宝编著.ERDAS IMAGINE遥感图像处理方法[M].清华大学出版社.2003.
[5]韦玉春,汤国安等编著.遥感数字图像处理教程[M].科学出版社.2007.
[6]徐春.基于遥感图像的交通信息提取研究与实现[D].北京:清华大学.2008.
[7]朱瑞芳.基于遥感影像的城市绿地信息提取方法研究[D].辽宁:辽宁工程技术大学.2005.
[8]刘桂生,葛根旺.基于遥感影像的土地利用监督分类探讨[J].城市勘测.2008(03):43-46
[9]薛辉,倪绍祥.居民地信息遥感提取方法比较研究[J].水土保持研究.2006,(05):319-321
[10]李国清.南方山地丘陵森林主要树种遥感信息提取研究[D].福建:福建农林大学.2009.
[11]陈姝,居为民.遥感图像分类方法及研究进展[J].河北农业科学. 2009, 13 (1): 143-146
[12]王国芳.遥感图像计算机分类方法的研究[J].山西农业科学.2009,37(10):39-41
[13]赵志刚,陈学佺.遥感图像分类的统计融合方法及性能分析[J].计算机工程.2000,(10):136-137
[14]马静.遥感图像分类方法的研究[D].山东:山东科技大学.2003.
[15]常海军.基于卫星遥感数据的森林信息自动提取技术研究[D].内蒙古:内蒙古大学.2007.
[16]吐热尼古丽,张晓帆.基于人工神经网络的遥感图像处理方法研究[J].重庆科技学院学报(自然科学版).2006,(03):79-82
[17]邵飞.基于人工神经网络的遥感影像变化信息提取方法研究[D].山东:山东科技大学.2006.
[18]于祥,赵冬至,张丰收,肖忠峰.基于神经网络的红树林景观特性遥感提取技术研究[J].海洋环境科学. 2007,(12):576-579
[19]李斯泽. ENVI,ERDAS,PCI,ER_Mapper的特点与统计分类[J].电脑知识与技术. 2008,(06):1776-1799
[20]张京红,刘安麟,李登科,邓凤东,卓静. ERDAS IMAGINE监督分类模板评价的研究[J].陕西气象.2004,(03):37-39
[21]宋丽玲.多源遥感图像融合的算法和研究[D].安徽:安徽理工大学.2009.
[22]孙昕.公路交通基础信息空间数据采集方法分析与研究[D].吉林:吉林大学. 2005.
[23]王海芹,杨燕,汪生燕.国外四大遥感软件影像分类过程及效果比较[J].地理空间信息. 2009,(10):153-155
[24]刘桂生,葛根.基于遥感影像的土地利用监督分类探讨[J].城市勘测.2008,(03):43-46
[25]赵冬泉,党安荣,陈吉宁.监督分类方法在图片资料专题信息提取中的应用研究[J].测绘通报.2006,(11):32-34
[26]杨鑫.浅谈遥感图像监督分类与非监督分类[J].四川地质学报. 2008,(09):251-254
[27]陈姝,居为民.遥感图像分类方法及研究进展[J].河北农业科学.2009,(01):143-146
[28]王国芳.遥感图像计算机分类方法的研究[J].山西农业科学.2009,(10):39-41
[29]郭志强,蔡嵩.彩色遥感图像分类算法及Matlab实现[J].武汉理工大学学报.2006,(01):108-111
[30]贾永红,张春森,王爱平.基于BP神经网络的多源遥感影像分类[J].西安科技学院学报.2001,(03):58-60
[31]张志涌.精通MATLAB 5.3版[M].北京:北京航空航天大学出版社. 2000.
[32]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[33] Tao,C.and W.Run-sheng,An Algorithm for Extracting Road Network from Multi-Band Remote Sensing Images.Journal of Software软件学报,2001.
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[2]李小娟,宫兆宁,刘晓萌,李静等编译. ENVI遥感影像处理教程[M].中国环境科学出版社. 2007.
[3]赵文吉,段福州,刘晓萌,徐智勇等编译. ENVI遥感影像处理专题与实践[M].中国环境科学出版社. 2007.
[4]党安荣,王晓栋,陈晓峰,张建宝编著.ERDAS IMAGINE遥感图像处理方法[M].清华大学出版社.2003.
[5]韦玉春,汤国安等编著.遥感数字图像处理教程[M].科学出版社.2007.
[6]徐春.基于遥感图像的交通信息提取研究与实现[D].北京:清华大学.2008.
[7]朱瑞芳.基于遥感影像的城市绿地信息提取方法研究[D].辽宁:辽宁工程技术大学.2005.
[8]刘桂生,葛根旺.基于遥感影像的土地利用监督分类探讨[J].城市勘测.2008(03):43-46
[9]薛辉,倪绍祥.居民地信息遥感提取方法比较研究[J].水土保持研究.2006,(05):319-321
[10]李国清.南方山地丘陵森林主要树种遥感信息提取研究[D].福建:福建农林大学.2009.
[11]陈姝,居为民.遥感图像分类方法及研究进展[J].河北农业科学. 2009, 13 (1): 143-146
[12]王国芳.遥感图像计算机分类方法的研究[J].山西农业科学.2009,37(10):39-41
[13]赵志刚,陈学佺.遥感图像分类的统计融合方法及性能分析[J].计算机工程.2000,(10):136-137
[14]马静.遥感图像分类方法的研究[D].山东:山东科技大学.2003.
[15]常海军.基于卫星遥感数据的森林信息自动提取技术研究[D].内蒙古:内蒙古大学.2007.
[16]吐热尼古丽,张晓帆.基于人工神经网络的遥感图像处理方法研究[J].重庆科技学院学报(自然科学版).2006,(03):79-82
[17]邵飞.基于人工神经网络的遥感影像变化信息提取方法研究[D].山东:山东科技大学.2006.
[18]于祥,赵冬至,张丰收,肖忠峰.基于神经网络的红树林景观特性遥感提取技术研究[J].海洋环境科学. 2007,(12):576-579
[19]李斯泽. ENVI,ERDAS,PCI,ER_Mapper的特点与统计分类[J].电脑知识与技术. 2008,(06):1776-1799
[20]张京红,刘安麟,李登科,邓凤东,卓静. ERDAS IMAGINE监督分类模板评价的研究[J].陕西气象.2004,(03):37-39
[21]宋丽玲.多源遥感图像融合的算法和研究[D].安徽:安徽理工大学.2009.
[22]孙昕.公路交通基础信息空间数据采集方法分析与研究[D].吉林:吉林大学. 2005.
[23]王海芹,杨燕,汪生燕.国外四大遥感软件影像分类过程及效果比较[J].地理空间信息. 2009,(10):153-155
[24]刘桂生,葛根.基于遥感影像的土地利用监督分类探讨[J].城市勘测.2008,(03):43-46
[25]赵冬泉,党安荣,陈吉宁.监督分类方法在图片资料专题信息提取中的应用研究[J].测绘通报.2006,(11):32-34
[26]杨鑫.浅谈遥感图像监督分类与非监督分类[J].四川地质学报. 2008,(09):251-254
[27]陈姝,居为民.遥感图像分类方法及研究进展[J].河北农业科学.2009,(01):143-146
[28]王国芳.遥感图像计算机分类方法的研究[J].山西农业科学.2009,(10):39-41
[29]郭志强,蔡嵩.彩色遥感图像分类算法及Matlab实现[J].武汉理工大学学报.2006,(01):108-111
[30]贾永红,张春森,王爱平.基于BP神经网络的多源遥感影像分类[J].西安科技学院学报.2001,(03):58-60
[31]张志涌.精通MATLAB 5.3版[M].北京:北京航空航天大学出版社. 2000.
[32]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
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