基于数据库方式的遥感图像库内容检索研究
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摘要
21世纪遥感技术、计算机技术、网络技术的快速发展,使得各领域研究者获取所需要的高精度、高分辨率、多时相遥感图像成为可能,但与之对应的却是遥感图像检索理论和技术的严重滞后。如何从海量遥感图像库中快速准确地检索到所需要的信息具有十分重要的意义。论文从遥感图像检索研究现状和存在的问题出发,发展了通用遥感图像概念模型URSICM,设计了面向对象的逻辑组织与数据存储方案,提出了融合颜色纹理特征CTFFBIR和基于GIS语义的遥感图像检索新方法,探讨了特征相似性检索的优化方案,设计并开发了原型系统RSIQuery,为遥感图像库的检索与管理提供新的思路。
论文主要研究内容如下:
(1)讨论了遥感图像库内容检索RSIDBCI的部分关键技术,包括:遥感图像数据的组织与管理方式、数据库索引机制、视觉特征描述与提取、相似性度量、相关反馈机制,以及检索算法评价等,并指出目前RSIDBCI面临的困难和存在的问题。
(2)通过对遥感图像所表达信息的特点、所包含的内容,以及现有图像数据模型的特点和局限的分析,提出一种通用的遥感图像概念模型URSICM,该模型将遥感图像的元数据、原始像元信息、视觉特征、图像对象、语义内容等信息纳入一个统一框架,并探讨了基于URSICM的面向对象的逻辑模型以及数据组织与存储方案。
(3)论述了图像分解的目的和意义,在分析四叉树和九叉树两种图像分解方法后,提出五叉树分解新方法,该方法整合四叉树和九叉树方法的优势,在子图像数目、以及查询图像与子图像的重叠率之间达到了一个较好的平衡。
(4)分析了单类视觉特征检索的不足,并根据高分辨率卫星与航空影像的光谱特点,提出一种融合颜色和纹理特征的遥感图像检索CTFFBIR新方法。该方法在利用多通道2D Gabor滤波器与图像做卷积得滤波能量值基础上,提取各子图像滤波能量纹理特征,计算子图像的颜色均值和均方差,对查询图像和与其大小相当的数据库子图像进行线性加权颜色和纹理特征距离相似性测度,其中特征的权重值可由查询者设置,也可通过相关反馈进行调整。
(5)为了提高CTFFBIR的检索效率,提出了基于聚类的子图像分类索引优化算法。该方法通过离线对数据库各子图像按26维颜色和纹理特征向量进行聚类,并按聚类结果对数据库子图像建立分类索引,从而极大地减少了在线检索的响应时间。
(6)提出了一种动态相关反馈算法,该算法采用适当改进Rui的多层特征权重更新方法的思路:各维、各类特征的权重在检索过程中通过对检索结果中子图像的相似性评分进行更新:前一轮被标上“不相关”的图像,不参与后续轮次的相似性测度;被标上“极相关”的图像,在后续轮次中具有优先排序号。
(7)提出了基于GIS语义的遥感图像检索GISSBIR方法,该方法通过直接借用GIS描述空间对象语义和空间关系的能力,检索出感兴趣对象,并用这些对象的最小边框读取对应的遥感图像数据空间范围,从而完成图像检索任务,为遥感图像库内容检索提供了一种可行的思路。GISSBIR研究主要侧重在以下两方面:一是为协调用户查询请求与系统之间的语义冲突,设计并构建了概念语义网络;二是为实现空间关系的检索,对Oracle Spatial的方向关系进行了扩展。
(8)设计并实现遥感图像库内容检索RSIQuery原型系统,该系统以Oracle为数据容器,以VC++为开发环境,采用分布式C/S架构实现。从试验结果分析来看,CTFFBIR及其优化算法是有效的,GISSBIR思路是可行的。
The fast development of remote sensing technology, computer technology and internet technology in 21st century is now making it possible for researchers from various disciplines to acquire needed multi-temporal remote sensing images with both high accuracy and high resolution. In contrast with this, there is a significant lag of the theory of remote sensing image retrieval as well as its relevant technologies. How to effectively obtain the needed information from massive remote sensing image-base is, therefore, of great importance. Starting from the status quo and some existing problems of remote sensing image retrieval, this dissertation aims to: (1)bring forward a universal remote sensing image concept model (URSICM), design a logical object-oriented organization and a data storage schema based on URSICM, (2)raise a new approach of the color and texture fused features based remote sensing image retrieval (CTFFBIR) and discuss the optimized algorithms of URSICM, (3)raise an approach of GIS semantics-based remote sensing image retrieval, (4) design and develop the prototype system RSIQuey, and (5)inject some new ideas into the retrieval and management of remote sensing image base.
Some main research contents are listed below:
1. The research discusses some critical technologies of remote sensing image -base content retrieval(RSIBCR), including the organization and management of remote sensing image data, the database indexing mechanism, the description and extraction of low-level vision features, the assessment of similarity between, the mechanism of relevance feedback and the evaluation of indexing algorithm. Some confronted difficulties and existing problems have also been identified.
2. By analyzing the information's characteristics, the contents provided by remote sensing image and the characteristics and limits of current image data models, this dissertation intends to introduce a universal concept model of remote sensing image data URSICM, which integrates the metadata of remote sensing images, raw pixel information, vision features, image objects and semantic contents into a unified frame, and discusses the URSICM-based logical object-oriented model, data organization and storage schema.
3. The research work demonstrates the purpose and significance of image decomposition. After examining the image decomposition methods of Quad-Tree and Nona-Tree, a method of Quin-Tree is put forward. This new method takes the advantages of both Quad-Tree and Nona-Tree, and reaches a more satisfactory balance between the quantity of sub-images and the overlapping ratio of query images and sub-images.
4. This dissertation also seeks to analyze the shortcomings of single type vision feature based retrieval and develops a new remote sensing image retrieval method of integrating color and texture fused features CTFFBIR, according to the spectral characteristics of satellite and aviation imagery with high resolution. Based on the use of filtering power values as the convolution of multi-channel 2D Gabor filters and the images, this new method exacts each sub-image's texture feature of filtering power, calculates average and mean square deviation of the color value of the subs-image, takes linear weighted similarity assessment from color and texture features' distance with query image and sub-images holding the same size from the database. In particular, the weighted feature value could be set by people sending the query request, and adjusted by relevant feedbacks.
5. In order to improve the retrieval efficiency of CTFFBIR, a cluster-based sub—image classifying indexing algorithm of optimization has been developed. This algorithm would largely reduce the response time of on-line qeuery by clustering each database's sub-images using their 26 dimensional feature of color and texture features and constructing the classifying index of database sub-images in use of the results of clustering.
6. An algorithm of dynamic relevance feedbacks is presented by the dissertation. The algorithm improves the Rui method of refreshing multi-level feature weights. The weight of different dimension and different class will be refreshed by evaluating the similarities of sub-images from indexing results during the process of image indexing. Images that have been labeled as uncorrelated in the previous round will not enter into the next similarity assessment, while the ones having been labeled as highly correlated will receive a number of high priority in the next round.
7. The dissertation also presents a GIS semantics-based method of remote sensing image retrieval(GISSBIR). This method is able to search for objects of interests by directly making use of GIS's capacity of describing spatial features and spatial relationships. By using the minimum border of these objects, the relevant geospatial scope of these remote sensing image data will be obtained, so that users can complete the task of indexing and produce an applicable alternative of remote sensing image database content indexing. GISSBIR puts special emphasis upon the following two questions: (1) constructing a conceptual semantic network to solve the semantic contradictions between user query request and the system, and (2) developing the retrieval of spatial relationships and making extensions for Oracle Spatial's direction relationship model.
8. The dissertation describes the design and implementation of the prototype system. Takes Oracle and Microsoft Visual C++ as its data container and developing platform, this system adapts a distributed architecture of Client/Server. By analyzing the experiment results, CTFFBIR and its optimum algorithm are essentially effective, and the thinking path is accessible.
论文主要研究内容如下:
(1)讨论了遥感图像库内容检索RSIDBCI的部分关键技术,包括:遥感图像数据的组织与管理方式、数据库索引机制、视觉特征描述与提取、相似性度量、相关反馈机制,以及检索算法评价等,并指出目前RSIDBCI面临的困难和存在的问题。
(2)通过对遥感图像所表达信息的特点、所包含的内容,以及现有图像数据模型的特点和局限的分析,提出一种通用的遥感图像概念模型URSICM,该模型将遥感图像的元数据、原始像元信息、视觉特征、图像对象、语义内容等信息纳入一个统一框架,并探讨了基于URSICM的面向对象的逻辑模型以及数据组织与存储方案。
(3)论述了图像分解的目的和意义,在分析四叉树和九叉树两种图像分解方法后,提出五叉树分解新方法,该方法整合四叉树和九叉树方法的优势,在子图像数目、以及查询图像与子图像的重叠率之间达到了一个较好的平衡。
(4)分析了单类视觉特征检索的不足,并根据高分辨率卫星与航空影像的光谱特点,提出一种融合颜色和纹理特征的遥感图像检索CTFFBIR新方法。该方法在利用多通道2D Gabor滤波器与图像做卷积得滤波能量值基础上,提取各子图像滤波能量纹理特征,计算子图像的颜色均值和均方差,对查询图像和与其大小相当的数据库子图像进行线性加权颜色和纹理特征距离相似性测度,其中特征的权重值可由查询者设置,也可通过相关反馈进行调整。
(5)为了提高CTFFBIR的检索效率,提出了基于聚类的子图像分类索引优化算法。该方法通过离线对数据库各子图像按26维颜色和纹理特征向量进行聚类,并按聚类结果对数据库子图像建立分类索引,从而极大地减少了在线检索的响应时间。
(6)提出了一种动态相关反馈算法,该算法采用适当改进Rui的多层特征权重更新方法的思路:各维、各类特征的权重在检索过程中通过对检索结果中子图像的相似性评分进行更新:前一轮被标上“不相关”的图像,不参与后续轮次的相似性测度;被标上“极相关”的图像,在后续轮次中具有优先排序号。
(7)提出了基于GIS语义的遥感图像检索GISSBIR方法,该方法通过直接借用GIS描述空间对象语义和空间关系的能力,检索出感兴趣对象,并用这些对象的最小边框读取对应的遥感图像数据空间范围,从而完成图像检索任务,为遥感图像库内容检索提供了一种可行的思路。GISSBIR研究主要侧重在以下两方面:一是为协调用户查询请求与系统之间的语义冲突,设计并构建了概念语义网络;二是为实现空间关系的检索,对Oracle Spatial的方向关系进行了扩展。
(8)设计并实现遥感图像库内容检索RSIQuery原型系统,该系统以Oracle为数据容器,以VC++为开发环境,采用分布式C/S架构实现。从试验结果分析来看,CTFFBIR及其优化算法是有效的,GISSBIR思路是可行的。
The fast development of remote sensing technology, computer technology and internet technology in 21st century is now making it possible for researchers from various disciplines to acquire needed multi-temporal remote sensing images with both high accuracy and high resolution. In contrast with this, there is a significant lag of the theory of remote sensing image retrieval as well as its relevant technologies. How to effectively obtain the needed information from massive remote sensing image-base is, therefore, of great importance. Starting from the status quo and some existing problems of remote sensing image retrieval, this dissertation aims to: (1)bring forward a universal remote sensing image concept model (URSICM), design a logical object-oriented organization and a data storage schema based on URSICM, (2)raise a new approach of the color and texture fused features based remote sensing image retrieval (CTFFBIR) and discuss the optimized algorithms of URSICM, (3)raise an approach of GIS semantics-based remote sensing image retrieval, (4) design and develop the prototype system RSIQuey, and (5)inject some new ideas into the retrieval and management of remote sensing image base.
Some main research contents are listed below:
1. The research discusses some critical technologies of remote sensing image -base content retrieval(RSIBCR), including the organization and management of remote sensing image data, the database indexing mechanism, the description and extraction of low-level vision features, the assessment of similarity between, the mechanism of relevance feedback and the evaluation of indexing algorithm. Some confronted difficulties and existing problems have also been identified.
2. By analyzing the information's characteristics, the contents provided by remote sensing image and the characteristics and limits of current image data models, this dissertation intends to introduce a universal concept model of remote sensing image data URSICM, which integrates the metadata of remote sensing images, raw pixel information, vision features, image objects and semantic contents into a unified frame, and discusses the URSICM-based logical object-oriented model, data organization and storage schema.
3. The research work demonstrates the purpose and significance of image decomposition. After examining the image decomposition methods of Quad-Tree and Nona-Tree, a method of Quin-Tree is put forward. This new method takes the advantages of both Quad-Tree and Nona-Tree, and reaches a more satisfactory balance between the quantity of sub-images and the overlapping ratio of query images and sub-images.
4. This dissertation also seeks to analyze the shortcomings of single type vision feature based retrieval and develops a new remote sensing image retrieval method of integrating color and texture fused features CTFFBIR, according to the spectral characteristics of satellite and aviation imagery with high resolution. Based on the use of filtering power values as the convolution of multi-channel 2D Gabor filters and the images, this new method exacts each sub-image's texture feature of filtering power, calculates average and mean square deviation of the color value of the subs-image, takes linear weighted similarity assessment from color and texture features' distance with query image and sub-images holding the same size from the database. In particular, the weighted feature value could be set by people sending the query request, and adjusted by relevant feedbacks.
5. In order to improve the retrieval efficiency of CTFFBIR, a cluster-based sub—image classifying indexing algorithm of optimization has been developed. This algorithm would largely reduce the response time of on-line qeuery by clustering each database's sub-images using their 26 dimensional feature of color and texture features and constructing the classifying index of database sub-images in use of the results of clustering.
6. An algorithm of dynamic relevance feedbacks is presented by the dissertation. The algorithm improves the Rui method of refreshing multi-level feature weights. The weight of different dimension and different class will be refreshed by evaluating the similarities of sub-images from indexing results during the process of image indexing. Images that have been labeled as uncorrelated in the previous round will not enter into the next similarity assessment, while the ones having been labeled as highly correlated will receive a number of high priority in the next round.
7. The dissertation also presents a GIS semantics-based method of remote sensing image retrieval(GISSBIR). This method is able to search for objects of interests by directly making use of GIS's capacity of describing spatial features and spatial relationships. By using the minimum border of these objects, the relevant geospatial scope of these remote sensing image data will be obtained, so that users can complete the task of indexing and produce an applicable alternative of remote sensing image database content indexing. GISSBIR puts special emphasis upon the following two questions: (1) constructing a conceptual semantic network to solve the semantic contradictions between user query request and the system, and (2) developing the retrieval of spatial relationships and making extensions for Oracle Spatial's direction relationship model.
8. The dissertation describes the design and implementation of the prototype system. Takes Oracle and Microsoft Visual C++ as its data container and developing platform, this system adapts a distributed architecture of Client/Server. By analyzing the experiment results, CTFFBIR and its optimum algorithm are essentially effective, and the thinking path is accessible.
引文
曹奎,冯玉才,曹忠升.彩色图像的联合分布表示及关键技术[J].中国图像图形学报,2001,6A(11):1084-1088.
曹奎、冯玉才.国产数据库DM3的图像引擎设计[J].小型微型计算机系统,2004,25(9):1644-1647.
陈常松,张传霞.GIS语义共享的实质及其实现途径[J].测绘科学,2000,25(1):29-33.
程昌秀、周成虎、陆锋.ArcInfo 8中面向对象空间数据模型的应用[J].地球信息科学,2002,3:86-90.
邓敏、李成名、刘文宝.利用拓扑和度量相结合的方法描述面目标间的空间关系[J].测绘学报,2002,31(2):164-169.
杜清运.空间信息的结构、表达及其理解机制[J].武汉测绘科技大学学报,1998,23(4):388-292.
段立娟、高文、林守勋等.图像检索中的动态相似性度量方法[J].计算机学报,2001,24(11):1-7.
樊昀、王润生.面向内容检索的彩色图像分割[J].计算机研究与发展.2002,39(3):376-381.
冯杭建.面向网络的海量空间数据库引擎研究与开发[D].硕士学位论文,200 4.
高锡章.基于大型数据库的海洋GIS设计与自主开发研究[D].博士学位论文,2004,52-77.
高永英、章毓晋、罗云.基于目标语义特征的图像检索系统[J].电子与信息学报,2003,25(10):1341-1348.
龚健雅,韩海洋.基于超地图原理的分布式空间数据模型[J].中国图象图形学报,2002,7A(7):688-692.
龚健雅.地理信息系统基础[M].北京:科学出版社,2001,70-121.
贡玉南,华建兴,黄秀宝.基于匹配Gabor滤波器的规则纹理缺陷检测方法[J].中国图像图形学报,2001,7,624-628.
黄杏元、汤勤.地理信息系统概论[M].北京:高等教育出版社,1989.
黄裕霞.基于元数据调解器的GIS语义互操作[J].中国图象图形学报,2002,8,7(A):851-857.
李德仁、龚健雅等.面向目标数据模型在地理属性数据库中的应用[J].武汉测绘科技大学学报,1991,16(4),1-8.
李德仁.数字地球与“三S”技术,地球空间信息技术与数字浙江分论坛论文集 (C).2000.11,1-5.
李金龙.基于认知的图像检索的若干理论与方法研究[DB/OL].万方数据库:博士学位论文,2003.
李琦、杨超伟、陈爱军.WebGIS中的地理关系数据库模型研究[J].中国图象图形学报,2000,5A(2):19-23.
李向阳,杨树元.颜色不变量的自适应聚类网络量化方法.中国图像图形学报,2002,7A(2):120-124.
李学龙、刘政凯、俞能海等.一种基于区域的动态分块图像检索方法[J].电路与系统学报,2002,7(1):47-51.
刘纪远、庄大方、凌杨荣.基于GIS的中国东北植被综合分类研究[J].遥感学报,1998,12(4):285-291.
刘南、刘仁义.地理信息系统[M].北京:高教出版社,2002.10.
刘仁义、刘南、苏国中.时空数据库基态修正模型的扩展[J].浙江大学学报,2000,27(3):196-200.
刘仁义、刘南.动态土地信息系统时空过程及时空数据存储[J].中国图形图象学报,2002,7(4):388-393.
刘仁义、刘南.一种基于数字高程模型DEM 的淹没区灾害评估方法[J].中国图形图象学报,2001,6(2):118-122.
刘仁义.面向网络的海量空间数据与时态空间数据模型及其应用研究[D].博士学位论文,2004.
陆丽珍、刘南、刘仁义.基于oo4o访问Oracle9i spatial空间数据[J].计算机工程与应用,2003,39(33):194-196.
陆丽珍、刘仁义、刘南.一种融合颜色和纹理特征的遥感图象检索方法[J].中国图象图形学报,2004,9(3):328-333.
陆丽珍.基于多通道Gabor纹理特征的遥感图象检索[J].浙江大学学报(理学版),2004,31(6):708-711.
罗睿,张永生,范永弘.遥感图象数据库基于内容查询的研究[J].遥感学报,2002,1,24-29.
萨师煊、王珊.数据库系统概论(第三版)[M].北京:高等教育出版社,2000.
施伯乐,丁宝康等.数据库技术[M].北京:科学出版社,2002.
宋晓军、李卓玲.Oracle系统中面向对象技术的应用[J].信息技术,2002,5:2-4.
田玉敏、乃学尚.基于整数小波变换的彩色图像检索技术的研究[J].中国图像图形学报,2002,7A(2):128-131.
汪祖媛、李斌、罗琳等.基于进化规划策略的纹理图像检索[J].小型微型计算机 系统,2001,8:950-953.
汪祖媛、梁栋、李斌等.基于树状小波分解的纹理图像检索[J].中国图像图形学报,2001,6A(6):1065-1069.
王惠锋、孙正兴、王箭.语义图像检索研究进展[J].计算机研究与发展,2002,39(5):513-522.
王家耀.空间信息系统原理[M],北京:科学出版社,2001,(4):158-160.
王密,龚健雅,基于扩展关系数据库的遥感影像数据库管理系统的研究与实现[J].测绘信息与工程,2002,10,1-3.
王熊斌.数据库系统教程[M].北京:电子工业出版社,2002,40.
邬伦、刘瑜、张晶等.地理信息系统原理、方法与应用[M].北京:科学出版社,2001.
肖乐斌、钟耳顺、刘纪远、宋关福.GIS空间概念模型的研究[DB/OL].2001.26.
肖乐斌、钟耳顺、刘纪远、宋关福GIS概念模型的研究[J].武汉大学学报(信息科学版),2001,26(5):387-392.
徐长勇,周焰,李德仁.基于内容的遥感图像检索综述[J].武汉理工大学学报(信息与管理工程版),2003,25(5):8-12.
易善帧,李琦,承继成.互操作GIS模型及其在空间基础设施体系结构中的实现途径[J].中国图象图形学报,1999,A(4):991-995.
尹劲峰.具有自主知识产权的通用遥感图像处理系统开发研究[D].硕士学位论文,2004.
袁昕,朱淼良.基于主色匹配的图像检索系统[J].计算机辅助设计与图形学学报,2000,12(12),7(1):11-42.
张斌、王国仁,郑还远.面向对象的多数据库系统中冲突的分类及解决策略[J].计算机研究与发展,1997,34(suppl.):300-304.
张继贤、李德仁.图像纹理的多尺度分析.环境遥感,1996,11(1):1-13.
张西宁,郑南宁.汽车牌照自动识别中的目标与背景的快速分割[J].信息与控制,1988,(2):27-31.
章毓晋,图像工程(上册)-图像处理和分析[M].北京:清华大学出版社,1999.
章毓晋.基于内容的视觉信息检索(M).北京:科学出版社,2003,1-9.
周成虎、骆剑承、杨晓梅等.遥感影像地学理解与分析[M].科学出版社,1999.
朱政.基于大型数据库的自主VR-GIS技术研究[D].硕士学位论文,2003.
庄越挺,潘云鹤,吴飞.网上多媒体信息分析与检索[M].清华大学出版社,2002,9-29.
Biederman I.On the semantics of a glance at a scene[C].In:Perceptual Organization.Hillsdale,NJ:Erlbaum,1981:213-253.
Abiteboul S,Hull R.IFO:A Formal semantic database model[J].ACM Transactions on Database Systems,1987,12(4):525-565.
(Adjeroh,2001) Adjeroh D A and Lee M C.On Ratio-Based Color Indexing[J].IEEE Trans.On Image Processing,2001,10(1):36-48.
Amoid W M,Marce W,Simone S,et al.Content-based image retrieval at the end of the early years[J].IEEE Trans on Pattern Analysis and Machine Intlligence,2000,22(12):1349-1379.
Bach J,Fuller C,GuptaA,and et al.Virage image search engine:an open framework for image management[C].In Proceedings of the SPIE,Storage and Retrieval for Image and Video Databases Ⅳ,San Jose,CA,1996,2,76-87.
Barros J,French J.Martin W,and et al.Using the triangle inequality to reduce the number of comparisons required for similarity-based retrieval[C].SPIE storage and retrieval for still image and video database Ⅳ,1996,2,233-237.
Beckman N,Kriegel H P.The R~*-tree:an efficient and robust access method for points and rectangles[C].Proc.Of the ACM SIGMOD conference on the Management of Data,1990,322-331.
Besag J.Spatial interaction and the statistical analysis of lattice systems[j].Journal of Royal Statistical Society,1974,36:192-236.
Biederman I.Aspects and extensions of a theory of human image understanding[C].In:Computational Processes in Human Vision:An Interdisciplinary perspective.Norwood,NJ:Ablex,1988:370-428.
Bimbo A.Visual information retrieval[M].Morgan Kaufmann Pulishers,1999.
Campell F and Green D,Optical and retina factors affecting visual resolution[J].J.Physiol.,1965,181:576-593.
Campell F and Kulikowski J.Orientation selectivity of the human visual system.J.Physiol,1966,197:437-441.
Carson C S et al.Region-based image querying[C].Proceedings ofIEEE Workshop on Content-Based Access of Image and Video Libraries,San Juan,Puerto Rico,1997:42-49.
Cavazza M,Green R J and Palmer I J.Multimedia Semantic Features and Image Content Description[C].Proceedings of MultiMedia Modeling,1998:39-46.
Chang N S,Fu K S.Query-by-pictorial example[J].IEEE Software Eng,1980,6(6):519-524.
Chang S K,Shi Q Y,Yan C W.Iconic indexing by 2-D strings[j].IEEE PAMI,1987,9(3):413-427.
Chen J,Li C M,Li Z L,et al.A Voronoi-based 9 intersection model for spatial relations[J].International Journal of Geographical Information Science,2001,15(3):201-220.
Chu W W,Fellow,and IEEE,et al.Knowledge-Based Image Retrieval with Spatial and Temporal Constructs[J].IEEE Transactions on Knowledge and Data Engineering,1998 10(6):872 -888.
Codd E.Extending the dataqbase relation model to capture more meaning[J].ACM Transactions on Database Systems,1979,4(4):397-434.
Coggins J M and Jain A K.A spatial filtering approach to texture analysis[J].Pattern Recognition Leters,1995,2:195-203.
Colombo C,Bimbo A and Pala P.Semantics in visual information retrieval[J].IEEE Multimedia,1999,6(3):38-53.
Date C J.An Introduction to Database Systems[M].The 6th edition,Reading:Addison-Wesley,Massachusetts,1995.
Date C J.An Introduction to Database Systems[M],Vol.Ⅱ.Reading,Ma:Addison-Wesley,1995.
Daugman.Complete discrete 2D Gabor transforms by neural networks for image analysis and compression[J].IEEE ASSP,1988,36(7):1169-1179.
Dori D,Hel-Or H.Semantic content based image retrieval using object-process diagrams[C].In:SSPR 1998.Sydney,Au:Springer,1998:15-30.
Dozier J,Stonebraker M,Frew J.Sequoia 2000:a next-generation information system for the study of global change[C].Mass Storage Systems,1994.'Towards Distributed Storage and Data Management Systems.' First International Symposium.Proceedings.,Thirteenth IEEE Symposium on,1994,6,12-16:47-53.
Eakins J P.Automatic image content retrieval Are we getting anywhere? In:Proc of 3rd Int'1 Conf on Electronic Library and Visual Information Research[C].De Montfort University,Milton Keynes:Aslib,1996,10(1):123-135.
Egenholfer M J,Franzosa D R.Point-set topological spatial relations[J].International Journal of GIS,1991,5(2):161-174.
Engenhofer M J.A Formal efinition of binary topological relationships[C].Proc.Of the third international conference on the foundations of data organixaion and algorithm,Poris,1989,124-130.
Engenhofer M,Franzosa R.On the equivalence of topological relations[J].I nternational Journal of Geographical Information Systems,1995,9(2):133-152.
ESRI Corporation.Getting started with SDE[M].An ESRI white paper,1997.
ETH Zurich.http://www.vision.ee.ethz.ch/-rsia/rsia2.html,2004.
Flickner M,Sawhney H,Niblack W,et al.Query by image and video content:the QBIC system[J].IEEE computer,1995,28(9):23-32.
Frank A U.Qualitative spatial reasoning about distances and directions in geographic space[J].J of Visual Languages and Computing,1992,3(4):343-371.
Freksa C,Barkokowsky T.On the relations between spatial concepts and geographic objects,in:Peter A B,Andrew U F.eds.Geographic objects with indeterminate boundaries[J].Taylor&Francis,1996,109-121.
(Fung,1999)Fung C Y,Loe K F.Learning primitive and scene semantics of images for classification and retrieval[C].Proc of the 7th ACM Int'1 Conf on Multimedia(part 2).Orlando,FL:ACM Press,1999:9-12.
Funt B V and Finlayson G D.Color constant color indexing[J].IEEE Trans.On PAMI,1995,522-529.
Gogolla W,Hohenstein U.Towards a semantic vies of an extended entity-relationship model[J].ACM Transactions on Database Systems,1991,16(3):369-416.
Gold C M.Problem with banding spatial data- the Voronoi approach[J].CISM Journal,1991,65-80.
Gong Y,Chus H,Gun X.Image Indexing and Retrieval Based on Color Histogram[J].Multimedia Modeling,Singapore,1995,11:115-126,
Gorkani M M,Picard R W.Texture orientation for sorting photos 'at A Glance'[J].IEEE Conf.On Pattern Recognition,MIT Technical Report 292,1994(1):459-464.
Grosky W I,et al.The handbook of multimedia information management[M].Prentice Hall PTR.1997.
Gudivada V,Raghavan V.Design and evaluation of algorithms for image retrieval by spatial similarity[J].ACM Trans on information systems,1995,13(1):115-144.
Guttman A.R-trees:a dynamic index structure for spatial searching[C].Proc.ACM SIGMOD,1984:47-57.
Hacid M S.Representing and reasoning on conceptual queries over image databases[j].Journal of intelligent information systems,2000,14,131-154.
Han J W and Guo L.A novel image retrieval technique based on salient edges[C].SPIE International Conference on Storage and Retrieval for Media Databases 2002,San Jose,California,USA,2002,6,46-76,
Haralick R M,Shan mugam K,Dinstein I.Texture features for image classification [J].IEEE Trans On Sys,Man and Cyb,1973,SMC-3(6):610-621.
Haralick R M.Statistical and structural approaches to texture[C].Proceedings of the IEEE,1979,67(5):786-804.
Hermes T,et al.Image retrieval for information systems[C].Storage and Retrieval for Image and Video Databases Ⅲ,Proc SPIE.1995,394-405.
Hill J,Megier J.Regional land cover and agriculture area statistics and mapping in department Ardeche,France,by use of thematic mapper data[J].International Journal of Remote Sensing,1988,9:1573-1595.
Holmes P D,Jungert E.Symbolic and geometric connectivity graph methods for reoute planning in digitized maps[J].IEEE PAMI,14(5):549-565,1992.
Hong P,Tian Q,and Huang T.Incorporate support vector machines to content-based image retrieval with relevance feedback[C].Proc.IEEE ICIP,2000(3):750-753.
Hsu C C,Chu W W,Taira R K,A knowledge-based approach for retrieving images by content[J].IEEE Trans on knowledge and data engineering,1996,8(4):522-532.
Huang J,Kumar S R,and Mitra M.Combining supervised learning with color correlograms for content-based image retrieval[C].ACM multimedia conference,1997:325-334.
Huang J,Kumar S R,Mitra M,et al.Image indexing using color correlograms[C].Proc.CVPR,1997:762-728.
Ishikawa Y,Subramanya R,and Faloutsos C.MindReader:Querying databases through multiple examples[C].Proc.VLDB,1998,8.
Jacobs C.E.Fast multi-resolution image querying[C].Proc.SIGGAPH,1995:277-286.
(Jain,1991) Jain A k,et al.Unsupervised Texture Segmentation Using Gabor Filters,Pattern Recognition[J],1991,12,24(24):1167-1186.
Jain A and Vailaya A.Image retrieval using color and shape[J].Patern Recognition,1996,29(8):1233-1244.
Jain A K,Vailaya A.Shape-based retrieval:a case study with trademark image databases[J].PR,31(9):1369-1390.
Jayaramamurthy S N.Texture disceimination using ditital de-convolution filters[C].Proc of SICPR,1980,1184-1186.
John R S,Li C S.Decoding image semantics using composite region templates[C].IEEE Workshop on Content-based Access of Image and Video Libraries(CBAIVL-98).Santa Barbara,California:IEEE CS Press,1998.9-11.
Julesz B.Texton gradients:the texton theory revisited[J].Biol.Cybern 1986,54:245-251.
Kato T.Database architecture for content-based image[C].SPIE,1992,1662,112-123.
Kitamoto A,Takagi M.Retrieval of Satellite Cloud Imagery Based on Subjective Similarity[C].Proceedings of the 9th Scandinavian Conference on Image Analysis(SCIA'95),1995,6,449-456.
Kuan J P K,Joyce DW,Lewis P H.Texture content based retrieval using text descriptions[C].SPIE,1999,3656:75-85.
Lawrence D B,Progressive Content-Based Retrieval from Satellite Image Archives[J/OL],D-Lib Magazine,1997,10.http://www.dlib.org/dlib/october97/ibm/101i.html.
Lee S Y,Hsu F J.Spatial reasoning and similarity retrieval of image using 2-D-C string knowledge representation[J].Pattern Recognition,1992,25(3):1077-1088.
Lee C,Ma W Y,Zhang H J.Information embedding based on user's relevance feedback for image retrieval[R].HP Labs:Technical Report,1998.
Li X L.Beauty and beast:image retrieval for image remodeling[C].Signal Processing and Information Technology,2003.ISSPIT 2003.Proceedings of the 3rd IEEE International Symposium on,2003,11,14-17,278-281.
Liu F,Picard R.Periodicity,directionality and randomness:wold features for image modeling and retrieval[J].IEEE-PAMI,1996,18(7):722-733.
Los Alamos National Laboratory.The CANDID Project 1994-1996[EB /OL].http://public.lanl.gov/kelly/CANDID/.2004-08-11.
Lu H,et al.Efficient Image Retrieval by Color Contents[C].Int'1.Conf.on Applications of DB,1994.
Lu Y et al.A unified framework for semantics and feature based relevance feedback in image retrieval systems[C].Process of ACM MM2000.Los Angeles,California:ACM Press,2000.31-38.
Manjunath B S and Ma WY.Texture features for browsing and retrieval of image data[J].IEEE Trans.On PAMI,1996,18(8):837-841.
Mao J and Jain A K.Texture classifictation and segmentatiton using multiresolution simultaneous autoregressive models[J].Pattern Recognition,1992,25(2):173-188.
University ofMaryland,MD,USA.Http://www.cs.umd.edu.users/vm/mm/viqs/.
Meghini C,Sebastiani F and Straccia U.The terminological image retrieval mode[C].In:Proc of CIAP'97,the 9th Int'1 Conf on Image Analysis and Processing Florence,IT:Springer Verlag,1997,156-163.
Mehtre B.M,Kankanhalli M.S and Lee W.F.Shape measures for content-based image retrieval:a comparison[C].Information Processing&Management.1997,33(3):319-337.
Meilhac C and Nastar C.Relevance feedback and category search in image databases[C].IEEE Conference on multimedia computing and systems,1999.
Minka M T.Machine Learning[C].McGraw Hill College Div,ISBN:0070428077,1997.
Molenaat M.Modeling topological relationship in vector maps[C].Waugh TC and Healey RG.The sixth international symposium on spatial data handling.London:Taylor & Rrancis,1996.
Ng R and Sedighian A.Evaluating multidimensional indexing structures for images transformed by principal component analysis[C].In Proc SPIE Storage and Retrieval for Image and Video Database,1996(2670):50-61.
Niblack W,et al.The QBIC project:querying images by content using color,texture,and shape[C].SPIE,1993,1908:173-187.
NTU school of computer Engineering,http://www.ntu.edu.sg/SCERNstaging/Aug2003/aug-art2.asp,2003,8.
Oge M,Furht B.MUSE:Content-Based Image Search and Retrieval System Using Relevance Feedback[J].Multimedia Tools and Applications.2002,17,21-50.
Ogle V E,Stonebraker M.Chabot:Retrieval from a relational database of images[J].IEEE Computer,1995,28(9):40-48.
Oracle Corp..Oracle Spatial User's Guide and Reference[M],1999.
Ortega M,Rui Y.Supporting Similarity Queries in MARS[J].ACM Multimedia,Seatle,WA,1997,11,325-231.
Papadias D,Sellis T.A pictorial query-by-example language[J].Journal of visual languages and computing,1995,6(1):53-72.
(Park,1999) Park I K,Yun I D,Lee S K,et al.Color image retrieval using hybrid graph representation[J].Image and Vision Computing,1999,17(7):465-474.
Pearlman W A.The art and practice of modern image compression[C].Keynote address,Visual Communications and Image Processing 2001,231-237.
Pentland A.Fractal-based description of natural scenes[J].IEEE Trans.On PAMI,1984,9:661-674.
Pentland A,Picard R.W and SclaroffS.Photobook:Content-based manipulation of image databases[R].Technical Report 255,MIT Media Lab Perceptual Computing,1993.
Peuquet D J,Zhan C X.An algorithm to determine the directional relationship between arbitrarily-shaped polygons in the plane[J].Pattern Recognition,1987,20(1):65-74.
Rabbitti R,Stanchev P.GRIM-DBMS:A graphical image database management system[C].Visual Database,Proc IFIP TC2/WG2.6 Working Conf on Visual Database System.Amsterdam Springer-Verlag,1989:415-530.
Remias E,Sheikholeslami G,Zhang A.Block-oriented image decomposition and retrieval in image database systems.Multimedia Database Management Systems,1996,Proceedings of International Workshop on,1996,8,14-16,85-92.
Remias E,Sheikholeslami G,Zhang A D.Supporting content-based retrieval in large image database systemsJ[J].Mutimedia Tools and Application.1997,4:153-170.
Rui Y and Huang T S.Optimizing Iearning in image retrieval[C].IEEE Conf.On CVPR,South Carolina,USA,2000,343-351.
Rui Y,Huang T S,Mehrotra S.Content-based image retrieval with relevance feedback in MARS[C].In:Proc IEEE International Conference on Image Proceeding,1997(2),815-818.
Rui Y,Huang T S and Mehrotra S.Relevance feedback:a powerful tool in interactive content-based image retrieval[J].IEEE Trans.On CSVT,1998,8(5):644-655.
Rui Y,Huang T S.A novel relevance feedback technique in image retrieval[C].ACM Multimedia 1999,434-438.
Samet H.A geographic information system using quadtrees[J].Pattern Recognition,1984,6:674-656.
Santini S,Jain R.Similarity match[J].IEEE Trans.On PAMI,1996,18(9):946-958.
Scassellati B.Retrieving images by-2D shape:a comparison of computation methods with human perceptual judgments[C].SPIE Proceeding,1994,2185:2-14.
Schaefer G.Compared domain indexing of losslessly compressed image[C].SPIE,2002,4676:79-85.
Schyns P G,Oliva A.From blobs to boundary edges:Evidence for time and spatial scale dependent scene recognition[J].Psychological Science,1994,5(2):195-200.
Sclaroff S,M L Cascia,Taycher L et al.Unifying textual and visual cues for content-based image retrieval on the World Wide Web[J].Computer Vision and Image Understanding,1999,75(1):86-98.
Sebe N,Lew M S.Texture features for content-based retrieval[C].In:Principles of Visual Information Retrieval.Springer Ch.2001,3:51-85.
Sellis T,Roussopulos N,Faloustos C.The R+ tree:A Dynamic Index for Multidimensional Objects[C].13th ConE on Very Large Databases,1987:507-518.
Sheikholeslami G,Zhang A D,A Multi-Resolution Content-Based Retrieva[J].Approach for Geographic Images GeoInformatica,1999,3:2,109-139.
Sheth A P,Larson J A.Federated databases systems for managing distributed heterogeneous,and autonomous databases[J].ACM computing surveys,1990,22(3):183-236.
Sheth A P,Bellcore.Semantic issues in multidatabase systems preface by the special issue editor[J].Sigmod Record,1991,20(4),5-9.
Siegel K,Madnick S.A metadata approach to resolving semantic conflicts[C].Proceeding of the 17th VLDB conference,Barcelona.Catolonia,Spain,1991:133-145.
Smeulders A W M,Worring M,Santini S,and et al.Content-based image retrieval at the end of the early years[J].IEEE Trans.On PAMI,2000,22(12):1349-1380.
Smith J.R and Chang S.E.VisualSEEK:A fully automated content-based image query system[C].In Proceedings of the 1996 ACM Multimedia Conference,Boston,MA,Nov.1996,87-98.
Smoulders A W M,Worring M,Santini S,et al.Content-Based Image Retrieval at the End of the Early Years[J].IEEE Trans.on PAMI,2000,22(12):1349-1380.
Stefanidis A,Agourls P.Sketch-based image retrieval in an integrated GIS environment[C].IAPRS,Stuttgart,1998,32:597-603.
Stricker M,Orengo M.Similarity of color images[C].SPIE,1995,2420:381-311.
Stricker M and Dimai A.Color indexing with weak spatial constraints in Storage and Retrieval for Image and Video Databases Ⅳ[C].Proc SPIE 2670,1996:29-40
Swain M J,Ballard D H.Color indexing[J].International Journal of Computer Vision.1991,7(1):11-32.
Szummer M,Picard R.Indoor-Outdoor Image Classification[C].Workshop in Content-Based Access to Image and Video Databases,Bombay,India,1998.
Tagare H.Increasing retrieval efficiency by index tree adaption[C].In Proc ofIEEE Workshop on Content-based Access of image and Vidieo Libraries,in conjunction with IEEE CVPR'97,1997,28-35.
Tamura H and Yokoya Naokazu.Image database system:A survey[J].Pattern Recognition,1984,17(1):29-43.
Tan K.L Ooi B.C,Yee C.Y.An evaluation of color-spatial retrieval techniques for large image databases[J].Multimedia Tools and Applications,2001,14,55-78.
Tang AY,Adams T,Usery E L.A Spatial Data Model Design for Feature-based Geographical Information Systems[J].Int.J.Geographical Information Systems,1996,10(5):643-659.
Tian Q,Hong P,and Huang T S.Update relevant image weights for content-based image retrieval using support vector machines[C].Proc.ICME,2000,2:1199-1202.
Tier K and Viola P.Boosting image retrieval[C].Proc of CVPR,2000.
Tong S and Chang E.Support vector machine active learning for image retrieval[C].Proc.ofACM Multimedia,Ottawa,Canada,2001.
Tuceryan M and Jain A K Texture segmentation using Voronoi polygons[J].IEEE Trans.On PAMI,1990,12:211-216.
Usnser M.Texture analysis and segmentation using wavelet frame[J].IEEE Trans.On Image Processing,1995,4(11):1549-1561.
Vailaya A.Semantic classification in image database[D].PhD Thesis,Dept.of Computer Science Michigan State University.2000.
Vailaya A,Figueiredo,Jain A K,et al.Image classification for content-based indexing[J].IEEE Trans on Image Processing,2001,10(1):117-130.
Veltkamp R C,Tanase M.Content-Based Image Retrieval Systems:A Survey[R].Technical Report W-CS-2000-34,2000,11.
Voorhees E.Using Wordnet to disambiguate word senses for text retrieval[C].In:Proc of the 16th Annual ACM SIGIR Conf on Research and Development in Information Retrieval.Pittsburgh:ACM Press,1993.171-180.
Wang Z,Chi Z,Feng D.Content-based image retrieval using block-constrained fractal coding and nona-tree decomposition Vision,Image and Signal Processing[C].IEEE Proceedings,2000,12,147(1):9-15.
Wang J Z,Li J,Wiederhold G.IMPLIcity:Semantics-sensitive integrated matching for picture libraries[J].IEEE Trans.On PAMI,23(8):947-963,2001,947-963.
Wei J.Color object indexing and retrieval in digital libraries[J].IEEE Trans.On Image 2002,912-922.
White D A,Jain R.Similarity indexing with the SS-tree[C].Proc.Of International Conf.On Data Engineering,1996,516-523
Wiederhold.Mediators in the architecture of future information system[J].IEEE computer,1992,25(3):38-49.
Wilkinson G G and Megier J.Evidential reasoning in a pixel classification hierarchya potential method for integrating image classification and wxpert system rules based on geographic context[J].Int.J.of Remote Sensing,11(10):1963-1968.
Wu Y,Zhuang Y T,Pan Y H.Image retrieval system for Web:Webscope-CBIR[C].IEEE Proc of the 11th Int'1 Workshop on Database and Export Systems Applications.Greenwich,London,UK:IEEE CS Press 2000:620-624.
Yaser B.Overcoming the semantic and the other barriers to GIS interoperability[J].IJGIS,1998,12(4):299-314.
Yates R B,Neto B R.Modern information retrieval[M].ACM Press,New York,1999.
Yiu E C.Image classification using color cues and texture orientation[D].Master's Thesis,MIT,Dept EECS,1996,20-25.
Yu H H,Wolf W.Scenic classification methods for image and video databases[C].SPIE:Digiatal image storage and archiving systems,1995:363-371.
Zhang C and Chen T.An active learning framework for content-based information retrieval[J].IEEE Trans.On Multimedia,2002,4(2):260-268.
Zhao R,Grosky W I.Narrowing the semantic gap-improved text-based Web document retrieval using visual features[J].IEEE Trans,Multimedia,2002(2):23-33.
Zhu B,Ramsey M,et al.Creating a Large-Scale Content-Based Airphoto Image Digital Library[C].IEEE Transaction on Image Processing,2000,1,9(1):163-167.
Papadias D,Theodoridis Y.Spatial relations,minimum bounding rectangles and spatial data structures[J].Int J Geographical information systems,1997,11(2):111-138.
曹奎、冯玉才.国产数据库DM3的图像引擎设计[J].小型微型计算机系统,2004,25(9):1644-1647.
陈常松,张传霞.GIS语义共享的实质及其实现途径[J].测绘科学,2000,25(1):29-33.
程昌秀、周成虎、陆锋.ArcInfo 8中面向对象空间数据模型的应用[J].地球信息科学,2002,3:86-90.
邓敏、李成名、刘文宝.利用拓扑和度量相结合的方法描述面目标间的空间关系[J].测绘学报,2002,31(2):164-169.
杜清运.空间信息的结构、表达及其理解机制[J].武汉测绘科技大学学报,1998,23(4):388-292.
段立娟、高文、林守勋等.图像检索中的动态相似性度量方法[J].计算机学报,2001,24(11):1-7.
樊昀、王润生.面向内容检索的彩色图像分割[J].计算机研究与发展.2002,39(3):376-381.
冯杭建.面向网络的海量空间数据库引擎研究与开发[D].硕士学位论文,200 4.
高锡章.基于大型数据库的海洋GIS设计与自主开发研究[D].博士学位论文,2004,52-77.
高永英、章毓晋、罗云.基于目标语义特征的图像检索系统[J].电子与信息学报,2003,25(10):1341-1348.
龚健雅,韩海洋.基于超地图原理的分布式空间数据模型[J].中国图象图形学报,2002,7A(7):688-692.
龚健雅.地理信息系统基础[M].北京:科学出版社,2001,70-121.
贡玉南,华建兴,黄秀宝.基于匹配Gabor滤波器的规则纹理缺陷检测方法[J].中国图像图形学报,2001,7,624-628.
黄杏元、汤勤.地理信息系统概论[M].北京:高等教育出版社,1989.
黄裕霞.基于元数据调解器的GIS语义互操作[J].中国图象图形学报,2002,8,7(A):851-857.
李德仁、龚健雅等.面向目标数据模型在地理属性数据库中的应用[J].武汉测绘科技大学学报,1991,16(4),1-8.
李德仁.数字地球与“三S”技术,地球空间信息技术与数字浙江分论坛论文集 (C).2000.11,1-5.
李金龙.基于认知的图像检索的若干理论与方法研究[DB/OL].万方数据库:博士学位论文,2003.
李琦、杨超伟、陈爱军.WebGIS中的地理关系数据库模型研究[J].中国图象图形学报,2000,5A(2):19-23.
李向阳,杨树元.颜色不变量的自适应聚类网络量化方法.中国图像图形学报,2002,7A(2):120-124.
李学龙、刘政凯、俞能海等.一种基于区域的动态分块图像检索方法[J].电路与系统学报,2002,7(1):47-51.
刘纪远、庄大方、凌杨荣.基于GIS的中国东北植被综合分类研究[J].遥感学报,1998,12(4):285-291.
刘南、刘仁义.地理信息系统[M].北京:高教出版社,2002.10.
刘仁义、刘南、苏国中.时空数据库基态修正模型的扩展[J].浙江大学学报,2000,27(3):196-200.
刘仁义、刘南.动态土地信息系统时空过程及时空数据存储[J].中国图形图象学报,2002,7(4):388-393.
刘仁义、刘南.一种基于数字高程模型DEM 的淹没区灾害评估方法[J].中国图形图象学报,2001,6(2):118-122.
刘仁义.面向网络的海量空间数据与时态空间数据模型及其应用研究[D].博士学位论文,2004.
陆丽珍、刘南、刘仁义.基于oo4o访问Oracle9i spatial空间数据[J].计算机工程与应用,2003,39(33):194-196.
陆丽珍、刘仁义、刘南.一种融合颜色和纹理特征的遥感图象检索方法[J].中国图象图形学报,2004,9(3):328-333.
陆丽珍.基于多通道Gabor纹理特征的遥感图象检索[J].浙江大学学报(理学版),2004,31(6):708-711.
罗睿,张永生,范永弘.遥感图象数据库基于内容查询的研究[J].遥感学报,2002,1,24-29.
萨师煊、王珊.数据库系统概论(第三版)[M].北京:高等教育出版社,2000.
施伯乐,丁宝康等.数据库技术[M].北京:科学出版社,2002.
宋晓军、李卓玲.Oracle系统中面向对象技术的应用[J].信息技术,2002,5:2-4.
田玉敏、乃学尚.基于整数小波变换的彩色图像检索技术的研究[J].中国图像图形学报,2002,7A(2):128-131.
汪祖媛、李斌、罗琳等.基于进化规划策略的纹理图像检索[J].小型微型计算机 系统,2001,8:950-953.
汪祖媛、梁栋、李斌等.基于树状小波分解的纹理图像检索[J].中国图像图形学报,2001,6A(6):1065-1069.
王惠锋、孙正兴、王箭.语义图像检索研究进展[J].计算机研究与发展,2002,39(5):513-522.
王家耀.空间信息系统原理[M],北京:科学出版社,2001,(4):158-160.
王密,龚健雅,基于扩展关系数据库的遥感影像数据库管理系统的研究与实现[J].测绘信息与工程,2002,10,1-3.
王熊斌.数据库系统教程[M].北京:电子工业出版社,2002,40.
邬伦、刘瑜、张晶等.地理信息系统原理、方法与应用[M].北京:科学出版社,2001.
肖乐斌、钟耳顺、刘纪远、宋关福.GIS空间概念模型的研究[DB/OL].2001.26.
肖乐斌、钟耳顺、刘纪远、宋关福GIS概念模型的研究[J].武汉大学学报(信息科学版),2001,26(5):387-392.
徐长勇,周焰,李德仁.基于内容的遥感图像检索综述[J].武汉理工大学学报(信息与管理工程版),2003,25(5):8-12.
易善帧,李琦,承继成.互操作GIS模型及其在空间基础设施体系结构中的实现途径[J].中国图象图形学报,1999,A(4):991-995.
尹劲峰.具有自主知识产权的通用遥感图像处理系统开发研究[D].硕士学位论文,2004.
袁昕,朱淼良.基于主色匹配的图像检索系统[J].计算机辅助设计与图形学学报,2000,12(12),7(1):11-42.
张斌、王国仁,郑还远.面向对象的多数据库系统中冲突的分类及解决策略[J].计算机研究与发展,1997,34(suppl.):300-304.
张继贤、李德仁.图像纹理的多尺度分析.环境遥感,1996,11(1):1-13.
张西宁,郑南宁.汽车牌照自动识别中的目标与背景的快速分割[J].信息与控制,1988,(2):27-31.
章毓晋,图像工程(上册)-图像处理和分析[M].北京:清华大学出版社,1999.
章毓晋.基于内容的视觉信息检索(M).北京:科学出版社,2003,1-9.
周成虎、骆剑承、杨晓梅等.遥感影像地学理解与分析[M].科学出版社,1999.
朱政.基于大型数据库的自主VR-GIS技术研究[D].硕士学位论文,2003.
庄越挺,潘云鹤,吴飞.网上多媒体信息分析与检索[M].清华大学出版社,2002,9-29.
Biederman I.On the semantics of a glance at a scene[C].In:Perceptual Organization.Hillsdale,NJ:Erlbaum,1981:213-253.
Abiteboul S,Hull R.IFO:A Formal semantic database model[J].ACM Transactions on Database Systems,1987,12(4):525-565.
(Adjeroh,2001) Adjeroh D A and Lee M C.On Ratio-Based Color Indexing[J].IEEE Trans.On Image Processing,2001,10(1):36-48.
Amoid W M,Marce W,Simone S,et al.Content-based image retrieval at the end of the early years[J].IEEE Trans on Pattern Analysis and Machine Intlligence,2000,22(12):1349-1379.
Bach J,Fuller C,GuptaA,and et al.Virage image search engine:an open framework for image management[C].In Proceedings of the SPIE,Storage and Retrieval for Image and Video Databases Ⅳ,San Jose,CA,1996,2,76-87.
Barros J,French J.Martin W,and et al.Using the triangle inequality to reduce the number of comparisons required for similarity-based retrieval[C].SPIE storage and retrieval for still image and video database Ⅳ,1996,2,233-237.
Beckman N,Kriegel H P.The R~*-tree:an efficient and robust access method for points and rectangles[C].Proc.Of the ACM SIGMOD conference on the Management of Data,1990,322-331.
Besag J.Spatial interaction and the statistical analysis of lattice systems[j].Journal of Royal Statistical Society,1974,36:192-236.
Biederman I.Aspects and extensions of a theory of human image understanding[C].In:Computational Processes in Human Vision:An Interdisciplinary perspective.Norwood,NJ:Ablex,1988:370-428.
Bimbo A.Visual information retrieval[M].Morgan Kaufmann Pulishers,1999.
Campell F and Green D,Optical and retina factors affecting visual resolution[J].J.Physiol.,1965,181:576-593.
Campell F and Kulikowski J.Orientation selectivity of the human visual system.J.Physiol,1966,197:437-441.
Carson C S et al.Region-based image querying[C].Proceedings ofIEEE Workshop on Content-Based Access of Image and Video Libraries,San Juan,Puerto Rico,1997:42-49.
Cavazza M,Green R J and Palmer I J.Multimedia Semantic Features and Image Content Description[C].Proceedings of MultiMedia Modeling,1998:39-46.
Chang N S,Fu K S.Query-by-pictorial example[J].IEEE Software Eng,1980,6(6):519-524.
Chang S K,Shi Q Y,Yan C W.Iconic indexing by 2-D strings[j].IEEE PAMI,1987,9(3):413-427.
Chen J,Li C M,Li Z L,et al.A Voronoi-based 9 intersection model for spatial relations[J].International Journal of Geographical Information Science,2001,15(3):201-220.
Chu W W,Fellow,and IEEE,et al.Knowledge-Based Image Retrieval with Spatial and Temporal Constructs[J].IEEE Transactions on Knowledge and Data Engineering,1998 10(6):872 -888.
Codd E.Extending the dataqbase relation model to capture more meaning[J].ACM Transactions on Database Systems,1979,4(4):397-434.
Coggins J M and Jain A K.A spatial filtering approach to texture analysis[J].Pattern Recognition Leters,1995,2:195-203.
Colombo C,Bimbo A and Pala P.Semantics in visual information retrieval[J].IEEE Multimedia,1999,6(3):38-53.
Date C J.An Introduction to Database Systems[M].The 6th edition,Reading:Addison-Wesley,Massachusetts,1995.
Date C J.An Introduction to Database Systems[M],Vol.Ⅱ.Reading,Ma:Addison-Wesley,1995.
Daugman.Complete discrete 2D Gabor transforms by neural networks for image analysis and compression[J].IEEE ASSP,1988,36(7):1169-1179.
Dori D,Hel-Or H.Semantic content based image retrieval using object-process diagrams[C].In:SSPR 1998.Sydney,Au:Springer,1998:15-30.
Dozier J,Stonebraker M,Frew J.Sequoia 2000:a next-generation information system for the study of global change[C].Mass Storage Systems,1994.'Towards Distributed Storage and Data Management Systems.' First International Symposium.Proceedings.,Thirteenth IEEE Symposium on,1994,6,12-16:47-53.
Eakins J P.Automatic image content retrieval Are we getting anywhere? In:Proc of 3rd Int'1 Conf on Electronic Library and Visual Information Research[C].De Montfort University,Milton Keynes:Aslib,1996,10(1):123-135.
Egenholfer M J,Franzosa D R.Point-set topological spatial relations[J].International Journal of GIS,1991,5(2):161-174.
Engenhofer M J.A Formal efinition of binary topological relationships[C].Proc.Of the third international conference on the foundations of data organixaion and algorithm,Poris,1989,124-130.
Engenhofer M,Franzosa R.On the equivalence of topological relations[J].I nternational Journal of Geographical Information Systems,1995,9(2):133-152.
ESRI Corporation.Getting started with SDE[M].An ESRI white paper,1997.
ETH Zurich.http://www.vision.ee.ethz.ch/-rsia/rsia2.html,2004.
Flickner M,Sawhney H,Niblack W,et al.Query by image and video content:the QBIC system[J].IEEE computer,1995,28(9):23-32.
Frank A U.Qualitative spatial reasoning about distances and directions in geographic space[J].J of Visual Languages and Computing,1992,3(4):343-371.
Freksa C,Barkokowsky T.On the relations between spatial concepts and geographic objects,in:Peter A B,Andrew U F.eds.Geographic objects with indeterminate boundaries[J].Taylor&Francis,1996,109-121.
(Fung,1999)Fung C Y,Loe K F.Learning primitive and scene semantics of images for classification and retrieval[C].Proc of the 7th ACM Int'1 Conf on Multimedia(part 2).Orlando,FL:ACM Press,1999:9-12.
Funt B V and Finlayson G D.Color constant color indexing[J].IEEE Trans.On PAMI,1995,522-529.
Gogolla W,Hohenstein U.Towards a semantic vies of an extended entity-relationship model[J].ACM Transactions on Database Systems,1991,16(3):369-416.
Gold C M.Problem with banding spatial data- the Voronoi approach[J].CISM Journal,1991,65-80.
Gong Y,Chus H,Gun X.Image Indexing and Retrieval Based on Color Histogram[J].Multimedia Modeling,Singapore,1995,11:115-126,
Gorkani M M,Picard R W.Texture orientation for sorting photos 'at A Glance'[J].IEEE Conf.On Pattern Recognition,MIT Technical Report 292,1994(1):459-464.
Grosky W I,et al.The handbook of multimedia information management[M].Prentice Hall PTR.1997.
Gudivada V,Raghavan V.Design and evaluation of algorithms for image retrieval by spatial similarity[J].ACM Trans on information systems,1995,13(1):115-144.
Guttman A.R-trees:a dynamic index structure for spatial searching[C].Proc.ACM SIGMOD,1984:47-57.
Hacid M S.Representing and reasoning on conceptual queries over image databases[j].Journal of intelligent information systems,2000,14,131-154.
Han J W and Guo L.A novel image retrieval technique based on salient edges[C].SPIE International Conference on Storage and Retrieval for Media Databases 2002,San Jose,California,USA,2002,6,46-76,
Haralick R M,Shan mugam K,Dinstein I.Texture features for image classification [J].IEEE Trans On Sys,Man and Cyb,1973,SMC-3(6):610-621.
Haralick R M.Statistical and structural approaches to texture[C].Proceedings of the IEEE,1979,67(5):786-804.
Hermes T,et al.Image retrieval for information systems[C].Storage and Retrieval for Image and Video Databases Ⅲ,Proc SPIE.1995,394-405.
Hill J,Megier J.Regional land cover and agriculture area statistics and mapping in department Ardeche,France,by use of thematic mapper data[J].International Journal of Remote Sensing,1988,9:1573-1595.
Holmes P D,Jungert E.Symbolic and geometric connectivity graph methods for reoute planning in digitized maps[J].IEEE PAMI,14(5):549-565,1992.
Hong P,Tian Q,and Huang T.Incorporate support vector machines to content-based image retrieval with relevance feedback[C].Proc.IEEE ICIP,2000(3):750-753.
Hsu C C,Chu W W,Taira R K,A knowledge-based approach for retrieving images by content[J].IEEE Trans on knowledge and data engineering,1996,8(4):522-532.
Huang J,Kumar S R,and Mitra M.Combining supervised learning with color correlograms for content-based image retrieval[C].ACM multimedia conference,1997:325-334.
Huang J,Kumar S R,Mitra M,et al.Image indexing using color correlograms[C].Proc.CVPR,1997:762-728.
Ishikawa Y,Subramanya R,and Faloutsos C.MindReader:Querying databases through multiple examples[C].Proc.VLDB,1998,8.
Jacobs C.E.Fast multi-resolution image querying[C].Proc.SIGGAPH,1995:277-286.
(Jain,1991) Jain A k,et al.Unsupervised Texture Segmentation Using Gabor Filters,Pattern Recognition[J],1991,12,24(24):1167-1186.
Jain A and Vailaya A.Image retrieval using color and shape[J].Patern Recognition,1996,29(8):1233-1244.
Jain A K,Vailaya A.Shape-based retrieval:a case study with trademark image databases[J].PR,31(9):1369-1390.
Jayaramamurthy S N.Texture disceimination using ditital de-convolution filters[C].Proc of SICPR,1980,1184-1186.
John R S,Li C S.Decoding image semantics using composite region templates[C].IEEE Workshop on Content-based Access of Image and Video Libraries(CBAIVL-98).Santa Barbara,California:IEEE CS Press,1998.9-11.
Julesz B.Texton gradients:the texton theory revisited[J].Biol.Cybern 1986,54:245-251.
Kato T.Database architecture for content-based image[C].SPIE,1992,1662,112-123.
Kitamoto A,Takagi M.Retrieval of Satellite Cloud Imagery Based on Subjective Similarity[C].Proceedings of the 9th Scandinavian Conference on Image Analysis(SCIA'95),1995,6,449-456.
Kuan J P K,Joyce DW,Lewis P H.Texture content based retrieval using text descriptions[C].SPIE,1999,3656:75-85.
Lawrence D B,Progressive Content-Based Retrieval from Satellite Image Archives[J/OL],D-Lib Magazine,1997,10.http://www.dlib.org/dlib/october97/ibm/101i.html.
Lee S Y,Hsu F J.Spatial reasoning and similarity retrieval of image using 2-D-C string knowledge representation[J].Pattern Recognition,1992,25(3):1077-1088.
Lee C,Ma W Y,Zhang H J.Information embedding based on user's relevance feedback for image retrieval[R].HP Labs:Technical Report,1998.
Li X L.Beauty and beast:image retrieval for image remodeling[C].Signal Processing and Information Technology,2003.ISSPIT 2003.Proceedings of the 3rd IEEE International Symposium on,2003,11,14-17,278-281.
Liu F,Picard R.Periodicity,directionality and randomness:wold features for image modeling and retrieval[J].IEEE-PAMI,1996,18(7):722-733.
Los Alamos National Laboratory.The CANDID Project 1994-1996[EB /OL].http://public.lanl.gov/kelly/CANDID/.2004-08-11.
Lu H,et al.Efficient Image Retrieval by Color Contents[C].Int'1.Conf.on Applications of DB,1994.
Lu Y et al.A unified framework for semantics and feature based relevance feedback in image retrieval systems[C].Process of ACM MM2000.Los Angeles,California:ACM Press,2000.31-38.
Manjunath B S and Ma WY.Texture features for browsing and retrieval of image data[J].IEEE Trans.On PAMI,1996,18(8):837-841.
Mao J and Jain A K.Texture classifictation and segmentatiton using multiresolution simultaneous autoregressive models[J].Pattern Recognition,1992,25(2):173-188.
University ofMaryland,MD,USA.Http://www.cs.umd.edu.users/vm/mm/viqs/.
Meghini C,Sebastiani F and Straccia U.The terminological image retrieval mode[C].In:Proc of CIAP'97,the 9th Int'1 Conf on Image Analysis and Processing Florence,IT:Springer Verlag,1997,156-163.
Mehtre B.M,Kankanhalli M.S and Lee W.F.Shape measures for content-based image retrieval:a comparison[C].Information Processing&Management.1997,33(3):319-337.
Meilhac C and Nastar C.Relevance feedback and category search in image databases[C].IEEE Conference on multimedia computing and systems,1999.
Minka M T.Machine Learning[C].McGraw Hill College Div,ISBN:0070428077,1997.
Molenaat M.Modeling topological relationship in vector maps[C].Waugh TC and Healey RG.The sixth international symposium on spatial data handling.London:Taylor & Rrancis,1996.
Ng R and Sedighian A.Evaluating multidimensional indexing structures for images transformed by principal component analysis[C].In Proc SPIE Storage and Retrieval for Image and Video Database,1996(2670):50-61.
Niblack W,et al.The QBIC project:querying images by content using color,texture,and shape[C].SPIE,1993,1908:173-187.
NTU school of computer Engineering,http://www.ntu.edu.sg/SCERNstaging/Aug2003/aug-art2.asp,2003,8.
Oge M,Furht B.MUSE:Content-Based Image Search and Retrieval System Using Relevance Feedback[J].Multimedia Tools and Applications.2002,17,21-50.
Ogle V E,Stonebraker M.Chabot:Retrieval from a relational database of images[J].IEEE Computer,1995,28(9):40-48.
Oracle Corp..Oracle Spatial User's Guide and Reference[M],1999.
Ortega M,Rui Y.Supporting Similarity Queries in MARS[J].ACM Multimedia,Seatle,WA,1997,11,325-231.
Papadias D,Sellis T.A pictorial query-by-example language[J].Journal of visual languages and computing,1995,6(1):53-72.
(Park,1999) Park I K,Yun I D,Lee S K,et al.Color image retrieval using hybrid graph representation[J].Image and Vision Computing,1999,17(7):465-474.
Pearlman W A.The art and practice of modern image compression[C].Keynote address,Visual Communications and Image Processing 2001,231-237.
Pentland A.Fractal-based description of natural scenes[J].IEEE Trans.On PAMI,1984,9:661-674.
Pentland A,Picard R.W and SclaroffS.Photobook:Content-based manipulation of image databases[R].Technical Report 255,MIT Media Lab Perceptual Computing,1993.
Peuquet D J,Zhan C X.An algorithm to determine the directional relationship between arbitrarily-shaped polygons in the plane[J].Pattern Recognition,1987,20(1):65-74.
Rabbitti R,Stanchev P.GRIM-DBMS:A graphical image database management system[C].Visual Database,Proc IFIP TC2/WG2.6 Working Conf on Visual Database System.Amsterdam Springer-Verlag,1989:415-530.
Remias E,Sheikholeslami G,Zhang A.Block-oriented image decomposition and retrieval in image database systems.Multimedia Database Management Systems,1996,Proceedings of International Workshop on,1996,8,14-16,85-92.
Remias E,Sheikholeslami G,Zhang A D.Supporting content-based retrieval in large image database systemsJ[J].Mutimedia Tools and Application.1997,4:153-170.
Rui Y and Huang T S.Optimizing Iearning in image retrieval[C].IEEE Conf.On CVPR,South Carolina,USA,2000,343-351.
Rui Y,Huang T S,Mehrotra S.Content-based image retrieval with relevance feedback in MARS[C].In:Proc IEEE International Conference on Image Proceeding,1997(2),815-818.
Rui Y,Huang T S and Mehrotra S.Relevance feedback:a powerful tool in interactive content-based image retrieval[J].IEEE Trans.On CSVT,1998,8(5):644-655.
Rui Y,Huang T S.A novel relevance feedback technique in image retrieval[C].ACM Multimedia 1999,434-438.
Samet H.A geographic information system using quadtrees[J].Pattern Recognition,1984,6:674-656.
Santini S,Jain R.Similarity match[J].IEEE Trans.On PAMI,1996,18(9):946-958.
Scassellati B.Retrieving images by-2D shape:a comparison of computation methods with human perceptual judgments[C].SPIE Proceeding,1994,2185:2-14.
Schaefer G.Compared domain indexing of losslessly compressed image[C].SPIE,2002,4676:79-85.
Schyns P G,Oliva A.From blobs to boundary edges:Evidence for time and spatial scale dependent scene recognition[J].Psychological Science,1994,5(2):195-200.
Sclaroff S,M L Cascia,Taycher L et al.Unifying textual and visual cues for content-based image retrieval on the World Wide Web[J].Computer Vision and Image Understanding,1999,75(1):86-98.
Sebe N,Lew M S.Texture features for content-based retrieval[C].In:Principles of Visual Information Retrieval.Springer Ch.2001,3:51-85.
Sellis T,Roussopulos N,Faloustos C.The R+ tree:A Dynamic Index for Multidimensional Objects[C].13th ConE on Very Large Databases,1987:507-518.
Sheikholeslami G,Zhang A D,A Multi-Resolution Content-Based Retrieva[J].Approach for Geographic Images GeoInformatica,1999,3:2,109-139.
Sheth A P,Larson J A.Federated databases systems for managing distributed heterogeneous,and autonomous databases[J].ACM computing surveys,1990,22(3):183-236.
Sheth A P,Bellcore.Semantic issues in multidatabase systems preface by the special issue editor[J].Sigmod Record,1991,20(4),5-9.
Siegel K,Madnick S.A metadata approach to resolving semantic conflicts[C].Proceeding of the 17th VLDB conference,Barcelona.Catolonia,Spain,1991:133-145.
Smeulders A W M,Worring M,Santini S,and et al.Content-based image retrieval at the end of the early years[J].IEEE Trans.On PAMI,2000,22(12):1349-1380.
Smith J.R and Chang S.E.VisualSEEK:A fully automated content-based image query system[C].In Proceedings of the 1996 ACM Multimedia Conference,Boston,MA,Nov.1996,87-98.
Smoulders A W M,Worring M,Santini S,et al.Content-Based Image Retrieval at the End of the Early Years[J].IEEE Trans.on PAMI,2000,22(12):1349-1380.
Stefanidis A,Agourls P.Sketch-based image retrieval in an integrated GIS environment[C].IAPRS,Stuttgart,1998,32:597-603.
Stricker M,Orengo M.Similarity of color images[C].SPIE,1995,2420:381-311.
Stricker M and Dimai A.Color indexing with weak spatial constraints in Storage and Retrieval for Image and Video Databases Ⅳ[C].Proc SPIE 2670,1996:29-40
Swain M J,Ballard D H.Color indexing[J].International Journal of Computer Vision.1991,7(1):11-32.
Szummer M,Picard R.Indoor-Outdoor Image Classification[C].Workshop in Content-Based Access to Image and Video Databases,Bombay,India,1998.
Tagare H.Increasing retrieval efficiency by index tree adaption[C].In Proc ofIEEE Workshop on Content-based Access of image and Vidieo Libraries,in conjunction with IEEE CVPR'97,1997,28-35.
Tamura H and Yokoya Naokazu.Image database system:A survey[J].Pattern Recognition,1984,17(1):29-43.
Tan K.L Ooi B.C,Yee C.Y.An evaluation of color-spatial retrieval techniques for large image databases[J].Multimedia Tools and Applications,2001,14,55-78.
Tang AY,Adams T,Usery E L.A Spatial Data Model Design for Feature-based Geographical Information Systems[J].Int.J.Geographical Information Systems,1996,10(5):643-659.
Tian Q,Hong P,and Huang T S.Update relevant image weights for content-based image retrieval using support vector machines[C].Proc.ICME,2000,2:1199-1202.
Tier K and Viola P.Boosting image retrieval[C].Proc of CVPR,2000.
Tong S and Chang E.Support vector machine active learning for image retrieval[C].Proc.ofACM Multimedia,Ottawa,Canada,2001.
Tuceryan M and Jain A K Texture segmentation using Voronoi polygons[J].IEEE Trans.On PAMI,1990,12:211-216.
Usnser M.Texture analysis and segmentation using wavelet frame[J].IEEE Trans.On Image Processing,1995,4(11):1549-1561.
Vailaya A.Semantic classification in image database[D].PhD Thesis,Dept.of Computer Science Michigan State University.2000.
Vailaya A,Figueiredo,Jain A K,et al.Image classification for content-based indexing[J].IEEE Trans on Image Processing,2001,10(1):117-130.
Veltkamp R C,Tanase M.Content-Based Image Retrieval Systems:A Survey[R].Technical Report W-CS-2000-34,2000,11.
Voorhees E.Using Wordnet to disambiguate word senses for text retrieval[C].In:Proc of the 16th Annual ACM SIGIR Conf on Research and Development in Information Retrieval.Pittsburgh:ACM Press,1993.171-180.
Wang Z,Chi Z,Feng D.Content-based image retrieval using block-constrained fractal coding and nona-tree decomposition Vision,Image and Signal Processing[C].IEEE Proceedings,2000,12,147(1):9-15.
Wang J Z,Li J,Wiederhold G.IMPLIcity:Semantics-sensitive integrated matching for picture libraries[J].IEEE Trans.On PAMI,23(8):947-963,2001,947-963.
Wei J.Color object indexing and retrieval in digital libraries[J].IEEE Trans.On Image 2002,912-922.
White D A,Jain R.Similarity indexing with the SS-tree[C].Proc.Of International Conf.On Data Engineering,1996,516-523
Wiederhold.Mediators in the architecture of future information system[J].IEEE computer,1992,25(3):38-49.
Wilkinson G G and Megier J.Evidential reasoning in a pixel classification hierarchya potential method for integrating image classification and wxpert system rules based on geographic context[J].Int.J.of Remote Sensing,11(10):1963-1968.
Wu Y,Zhuang Y T,Pan Y H.Image retrieval system for Web:Webscope-CBIR[C].IEEE Proc of the 11th Int'1 Workshop on Database and Export Systems Applications.Greenwich,London,UK:IEEE CS Press 2000:620-624.
Yaser B.Overcoming the semantic and the other barriers to GIS interoperability[J].IJGIS,1998,12(4):299-314.
Yates R B,Neto B R.Modern information retrieval[M].ACM Press,New York,1999.
Yiu E C.Image classification using color cues and texture orientation[D].Master's Thesis,MIT,Dept EECS,1996,20-25.
Yu H H,Wolf W.Scenic classification methods for image and video databases[C].SPIE:Digiatal image storage and archiving systems,1995:363-371.
Zhang C and Chen T.An active learning framework for content-based information retrieval[J].IEEE Trans.On Multimedia,2002,4(2):260-268.
Zhao R,Grosky W I.Narrowing the semantic gap-improved text-based Web document retrieval using visual features[J].IEEE Trans,Multimedia,2002(2):23-33.
Zhu B,Ramsey M,et al.Creating a Large-Scale Content-Based Airphoto Image Digital Library[C].IEEE Transaction on Image Processing,2000,1,9(1):163-167.
Papadias D,Theodoridis Y.Spatial relations,minimum bounding rectangles and spatial data structures[J].Int J Geographical information systems,1997,11(2):111-138.
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