Please wait a minute...
img

官方微信

遥感技术与应用  2010, Vol. 25 Issue (5): 619-626    DOI: 10.11873/j.issn.1004-0323.2010.5.619
图像处理     
异源、同源传感器影像融合的比较研究
林丽娟,徐涵秋,陈静洁,林冬凤,杜丽萍
(福州大学环境与资源学院,福州大学遥感信息工程研究所,福建 福州 350108)
Study on the Camparison of Image Fusion for the Same-source and Different-source Sensor
LIN Li-juan,XU Han-qiu,CHEN Jing-jie,LIN Dong-feng,DU Li-ping
 (College of Environment and Resources,Institute of Remote Sensing Information Engineering,
Fuzhou University,Fuzhou 350108,China)
 全文: PDF(1958 KB)  
摘要:

遥感影像的融合是遥感界的一个研究热点。根据数据源的不同,影像融合可分为异源传感器影像融合和同源传感器影像融合。以TM与SPOT作为异源影像融合的例子,以IKONOS的MS与Pan作为同源影像融合的例子,用5种算法对两种融合类型进行实验与比较。结果表明,同源传感器影像的融合效果好于异源传感器影像的融合效果;不同的融合算法在异源和同源传感器影像融合中的表现不尽相同。SVR变换可同时应用于异源及同源传感器影像的融合,且在提高影像空间分辨率、信息量和清晰度的同时能很好地保持原始多光谱影像的光谱特征。SFIM虽然也可以在两种数据源的融合实验中获得较好的融合效果,但其高频信息融入度最差。MB虽然提高了融合影像的高频信息融入程度,但光谱保真度、信息量和清晰度却不理想。Ehlers适用于异源传感器影像间的融合,而WT则适用于同源传感器影像的融合。

关键词: 遥感影像融合光谱保真度高频信息融入度    
Abstract:

Satellite image fusion is always a focus in remote sensing field.According to data sources difference,image fusion can be divided into two broad categories:fusion of images using different sensors data and using same sensor data.Five recently proposed/modified fusion algorithms have been employed to test the fusion results of the two categories.The image pair,TM+ SPOT pan,was used to test fusion between different image sources,while the pair,IKONOS MS+ pan,was employed to test fusion between same sensor data.The study reveals that the overall results of fusion between same sensor data are better than those of fusion between different sensors image sources.The selected fusion algorithms have different performance in image fusion results between the two categories.The SVR transform is suitable for both categories of image fusion.It can greatly improve the spatial resolution,information quantity and clarity,but retain spectral information of the original multispectral image.The SFIM\|fused image has the highest spectral fidelity in both categories of image fusion,but has the lowest spatial frequency information gain.Although the MB transform can improve the spatial resolution of the original image,it generally failed to improve spectral fidelity,information quantity and clarity.The Ehlers transform is more suitable for image fusion between different sensors data while the WT is more applicable to image fusion between same sensor data.

Key words: Remote sensing    Image fusion    Spectral fidelity    High spatial frequency information gain
收稿日期: 2010-02-26 出版日期: 2013-10-30
基金资助:

国家自然科学基金项目(40371107)、福建省教育厅重点项目(JK2009004)资助。

通讯作者: 徐涵秋(1955- ),教授,博士,博士生导师,主要从事环境资源遥感应用研究。E-mail:hxu@fzu.edu.cn。   
作者简介: 林丽娟(1985- ),女,硕士研究生,从事环境与资源遥感研究。E-mail:linlijuan133@yahoo.com.cn。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
林丽娟
徐涵秋
陈静洁
林冬凤
杜丽萍

引用本文:

林丽娟, 徐涵秋, 陈静洁, 林冬凤, 杜丽萍. 异源、同源传感器影像融合的比较研究[J]. 遥感技术与应用, 2010, 25(5): 619-626.

LIN Li-Juan, XU Han-Qiu, CHEN Jing-Jie, LIN Dong-Feng, DU Li-Ping. Study on the Camparison of Image Fusion for the Same-source and Different-source Sensor. Remote Sensing Technology and Application, 2010, 25(5): 619-626.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2010.5.619        http://www.rsta.ac.cn/CN/Y2010/V25/I5/619

[1]Zhou J,Civco D L,Silander J A.A Wavelet Transform Method to Merge Landsat TM and SPOT Panchromatic Data[J].International Journal of Remote Sensing,1998,19(4):743-757.
[2]Chen Dechao,Zhou Haibo,Chen Zhongyuan,et al.Study on Fusion Algorithms of TM and SPOT Images[J].Remote Sensing Technology and Application,2001,16(2):110-115.[陈德超,周海波,陈中原,等.TM与SPOT影像融合算法比较研究[J].遥感技术与应用,2001,16(2):110-115.]
[3]Xiao Ao,Tao Shu,Wang Xiaoshuang,et al.Remote Sensing Analysis and Evaluation of Fusion[J].Journal of Capital Normal University (Natural Science Edition),2007,28(4):77-80.[肖奥,陶舒,王晓爽,等.遥感融合方法分析与评价[J].首都师范大学学报(自然科学版),2007,28(4):77-80.]
[4]Li Hongjie,Dai Fuchu,Xu Ling,et al.The Assessment of Fused Image of ETM+ and SPOT5 Pan in the Investigation of Geological Hazards[J].Remote Sensing for Land & Resources,2008,(1):43-45.[李宏杰,戴福初,许领,等.地质灾害调查中ETM+与SPOT5 Pan影像融合与评价[J].国土资源遥感,2008,(1):43-45.]
[5]Liu J G.Evaluation of Landsat-7 ETM+ Panchromatic Band for Image Fusion with Multispectral Bands[J].Natural Resources Research,2000,9(4):269-276.
[6]Sun Danfeng.Study on Fusion Algorithms of IKONOS Pan and Multi-spectral Images[J].Remote Sensing Technology and Application,2002,17(1):41-45.[孙丹峰.IKONOS 全色与多光谱数据融合方法的比较研究[J].遥感技术与应用,2002,17(1):41-45.]
[7]Xu Rongfeng,Xu Hanqiu.Evaluation on Image Fusion Algorithms of Landsat-7 ETM+ Pan Band and Multispectral Bands[J].Geo-information Science,2004,6(1):99-104.[许榕峰,徐涵秋.ETM+全色波段及其多光谱波段图像的融合应用[J].地球信息科学,2004,6(1):99-104.]
[8]Wang Z J,Ziou D,Armenakis C,et al.A Comparative Analysis of Image Fusion Methods[J].IEEE Transactions on Geosciences and Remote Sensing,2005,43(6):1391-1402.
[9]Yu Junming,Zhou Yi,Wang Shixin,et al.Evaluation and Analysis on Image Fusion of ETM+[J].Remote Sensing Technology and Application,2007,22(6):733-738.[于君明,周艺,王世新,等.ETM+影像融合的评价分析[J].遥感技术与应用,2007,22(6):733-738.]
[10]Xu Hanqiu.Study on Data Fusion and Classification of Landsat 7 ETM+ Imagery[J].Journal of Remote Sensing,2005,2(9):186-194.[徐涵秋.Landsat7 ETM+影像的融合和自动分类研究[J].遥感学报,2005,2(9):186-194.]
[11]Xu Hanqiu.Classification of Fused Imagery Base on the SFIM Algorithm[J].Geomatics and Information Science of Wuhan University,2004,29(10):920-923.[徐涵秋.基于SFIM算法的融合影像分类研究[J].武汉大学学报·信息科学版,2004,29(10):920-923.]
[12]Zhang Y.A New Merging Method and Its Spectral and Spatial Effects[J].International Journal of Remote Sensing,1999,20(10):2003-2014.
[13]Zhao Yingshi.The Principle and Method of Analysis of Remote Sensing Application[M].Beijing:Science Press,2003:261-262.[赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003:261-262.]
[14]Ehlers M.Multisensor Image Fusion Techniques in Remote Sensing[J].ISPRS Journal of Photogrammetry and Remote Sensing,1991,46:19-30.
[15]Xu H Q.Evaluation of Two Absolute Radiometric Normalization Algorithms for Pre-processing of Landsat Imagery[J].Journal of China University of Geosciences,2006,17(2):146-150.
[16]Bretschneider T,Kao O.Image Fusion in Remote Sensing[C/OL]//Proceedings of the 1st Online Symposium of Electronic Engineers,2000,1-8,http://www.ntu.edu.sg/home/astimo.
[17]Shannon C E.A Mathematical Theory of Communication[M].Shanghai:Shanghai Science and Technology Commission,1965.[Shannon C E.通信的数学理论[M].上海:上海市科学技术编译馆,1965.]

 

[1] 郭擎,朱丽娅,李安,顾铃燕. 基于NDVI变化检测的滑坡遥感精细识别[J]. 遥感技术与应用, 2022, 37(1): 17-23.
[2] 杨凤珠,王震山,张乾,孙善磊,柳艺博. 多源日光诱导叶绿素荧光产品在中国地区的一致性研究[J]. 遥感技术与应用, 2022, 37(1): 125-136.
[3] 徐艳豪,丁忠昊,宋立生. TSEB模型在复杂下垫面下模拟结果比较研究[J]. 遥感技术与应用, 2022, 37(1): 85-93.
[4] 李翔华,黄春林,侯金亮,韩伟孝,冯娅娅,陈彦四,王静. 结合遥感和统计数据的家畜分布网格化方法研究[J]. 遥感技术与应用, 2022, 37(1): 262-271.
[5] 王茜,宋开山,毛德华,焉恒琦,谭晓宇,王宗明. 1980~2018朝鲜半岛西海岸滨海湿地演化分析[J]. 遥感技术与应用, 2022, 37(1): 108-116.
[6] 张红月,李宜展,陈思明,黄铭瑞,孙玉. 近10 a全球遥感科学研究的时空动态分析[J]. 遥感技术与应用, 2022, 37(1): 45-60.
[7] 黄耀欢,熊标,杨海军,伍程斌,朱海涛. 入河排污口遥感排查进展评述[J]. 遥感技术与应用, 2022, 37(1): 24-33.
[8] 赵天玮,朱文彬,裴亮,宝康妮. 三江源蒸散发遥感估算及其时空分布特征研究[J]. 遥感技术与应用, 2022, 37(1): 137-147.
[9] 赵辉,王泽根,雷光斌,边金虎,李爱农. 缅甸土地覆被遥感制图和空间格局分析[J]. 遥感技术与应用, 2022, 37(1): 148-160.
[10] 李杰,贾坤,张宁,魏香琴,王冰. 基于遥感与生态服务模型的青岛市生态保护重要性评价[J]. 遥感技术与应用, 2021, 36(6): 1329-1338.
[11] 梁立锋,谭本华,马咏珊,陈漾漾,刘秀娟. 基于多源地理大数据的城市空间结构研究[J]. 遥感技术与应用, 2021, 36(6): 1446-1456.
[12] 尹芳,封凯,吴朦朦,拜得珍,王蕊,周园园,尹春涛,尹翠景,刘磊. 一种基于分段偏最小二乘模型的土壤重金属遥感反演方法[J]. 遥感技术与应用, 2021, 36(6): 1321-1328.
[13] 陈喆,董庆,陈建平,赵文博,蒋良文,张广泽,冯涛,王栋,毕晓佳,边民,张权平,孟德利. 基于热红外遥感的川藏铁路昌都—林芝段地热异常区定量预测评价研究[J]. 遥感技术与应用, 2021, 36(6): 1368-1378.
[14] 张欢,李弘毅,李浩杰,车涛. 基于机载LiDAR的高寒山区遥感高程数据精度评估[J]. 遥感技术与应用, 2021, 36(6): 1311-1320.
[15] 王昀琛,黄春林,冯娅娅,顾娟. 基于2030可持续发展目标的珠三角土地消耗率与人口增长率协调关系评价[J]. 遥感技术与应用, 2021, 36(5): 1168-1177.