Please wait a minute...
img

官方微信

遥感技术与应用  2010, Vol. 25 Issue (1): 143-148    DOI: 10.11873/j.issn.1004-0323.2010.1.143
图像处理     
ASTER多光谱影像与资源二号全色影像融合研究
董张玉1,赵 萍2,胡文亮1
1.安徽师范大学国土资源与旅游学院,安徽 芜湖  241000;
2.合肥工业大学资源与环境工程学院,安徽 合肥 230009
Research on Fusion of ASTER Multi-spectral Image and Resources-2 Panchromatic Image
DONG Zhang-yu1,ZHAO Ping2,HU Wen-liang1
1.Territorial Resources and Tourism,Anhui Normal University,Wuhu 241000,China;
2.College of Resources and Environmental Engineerng,Hefei University of Technology,Hefei 230009,China)
 全文: PDF(2427 KB)  
摘要:

随着遥感获取数据手段的日益增多,遥感影像的融合技术备受关注。针对ASTER多光谱影像光谱信息丰富、分辨率小,资源二号全色影像分辨率高、纹理信息丰富的特点,以安徽省马鞍山市当涂县的ASTER多光谱影像与资源二号全色影像为例,分别采用基于主成分分析、小波变换以及主成分分析与小波变换相结合的3种融合方法进行融合实验,并对融合后的影像进行对比,探讨 ASTER多光谱影像与资源二号全色影像融合的方法和效果。结果表明:采用主成分分析与小波变换相结合的方法对两幅影像融合的效果最好,极大地改善了两种单一方法的缺点,提高了原始影像的目视效果和光谱信息,从而为区域研究提供了更精确的数据资料。

关键词: 小波变换主成分变换影像融合资源二号ASTER多光谱影像    
Abstract:

Remote sensing image fusion technology is concerned as the ways to obtain the RS data are growing.Aiming at the characteristics of multi-spectral imaging with more spectral information,Low-resolution and Resource-2 panchromatic images with high-resolution,rich texture information,this article,taking the ASTER multi-spectral image and Resources-2 panchromatic image of Dangtu County in Maanshan,Anhui Province as a case,discusses the fusion methods and effects of two kinds of images using three fusion methods based on principal component transformation,wavelet transform as well as principal component transformation combination with wavelet transform respectively,and comparing three fused images.The results show that the method based on principal component transformation combination with wavelet transform owns the best integration effect.It greatly overcomes the shortcoming of the fusion methods based on single transformation,and improves the visual effects and spectral information of the original image to provide more precise data for regional research.

Key words: Wavelet transform    PCA;Image fusion    Resources-2 panchromatic image    ASTER multi-spectral image
收稿日期: 2008-12-03 出版日期: 2011-11-04
基金资助:

国家自然科学基金项目(40771207);安徽省教育厅自然科学基金项目(KJ2007B219);安徽省教育厅教学项目(2007JYXM208);合肥工业大学博士学位专项资助基金和合肥工业大学科学研究发展基金(GDBJ2009-044)。

通讯作者: 赵萍 E-mail:njuzhp@sina.com   
作者简介: 董张玉(1986-),男,硕士研究生,研究方向为遥感数字影像处理。E-mail:dzyhh1988@126.com。
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  
董张玉
赵萍
胡文亮

引用本文:

董张玉, 赵萍, 胡文亮. ASTER多光谱影像与资源二号全色影像融合研究[J]. 遥感技术与应用, 2010, 25(1): 143-148.

DONG Zhang-yu, ZHAO Ping, HU Wen-liang. Research on Fusion of ASTER Multi-spectral Image and Resources-2 Panchromatic Image. Remote Sensing Technology and Application, 2010, 25(1): 143-148.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2010.1.143        http://www.rsta.ac.cn/CN/Y2010/V25/I1/143

[1]Jensen J R.Introductory Digital Image Processing a Remote Sensing Perspective[J].Pearson Education,2005,3:151-172.
[2]Zhao Yingshi.Principles and Methods of Remote Sensing Application Analysis[M].Beijing:Science Press,2002.[赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2002.]
[3]Mou Fengyun,Zhu Boqin.Research on the Fusion of Multi-source Remotely Sensed Data Based on Wavelat Transform[J].Remote Sensing of Land and Resources,2003,10(4):30-33.[牟凤云,朱博勤.基于小波变换的多源遥感数据融合方法研究[J].国土资源遥感,2003,10(4):30-33.]
[4]Gao Wentao,Wang Xiaoqin.Study for SAR and Optical Images Based on Wavelet Transform[J].Earth Information Science,2007,9(4):129-132.[高文涛,汪小钦.雷达与光学影像小波融合方法研究[J].地球信息科学,2007,9(4):129-132.]
[5]Zhang Dengrong,Yu Le.A Fusion Algorithm of Image Based on Wavelet Package and Different Frequencies Processing[J].Remote Sensing Information,2007,23(1):7-9.[张登荣,俞乐.基于小波包变换的分频影像融合方法[J].遥感信息,2007,23(1):7-9.]
[6]Dong Yumin.The Study of RS Data Fusion Based on Principal Component Transform with Additive Wavelet[J].Northeast Geomatics,2002,25(3):10-11.[董毓敏.基于小波叠加的主成分变换遥感数据融合方法的研究[J].东北测绘,2002,25(3):10-11.]
[7]Lin Hui,Jing Haitao,Zhang Lianpeng.Remote Sensing Images Fusion Based on a′ Trous Wavelet and PCA Transformation[J].Earth Information Science,2008,10(2):269-271.[林卉,景海涛,张连蓬.a′Trous小波变换与PCA变换相结合的遥感影像融合分析[J].地球信息科学,2008,10(2):269-271.]
[8]Zhao Wenhui,Zhao Wenji.Research on the Change of Land Use Types in Guyang Based on RS&GIS[J].Geomatics & Spatial Information Technology,2008,31(1):52-57.[赵文慧,赵文吉.基于 RS与GIS的固阳县土地利用变化研究[J].测绘与空间地理信息,2008,31(1):52-57.]
[9]Mei Anxin,Qin Qiming,Liu Huiping,et al.An Introduction Remote Sensing[M].Beijing:Higher Education Press,2001,196-237.[梅安新,秦其明,刘慧平,等.遥感导论[M].北京:高等教育出版社,2001,196-237.]
[10]Zhou Qianxiang,Jing Zhongliang.The Design and Application of Object-oriented Remote Sensing Image Fusion System[J].Remote Sensing Technology and Application,2004,19(1):15-17.[周前祥,敬忠良.面向对象的遥感影像融合处理系统的设计与应用[J].遥感技术与应用,2004,19(1):15-17.]
[11]Xu Lihua,Yue Wenze.A Study on the TM Classification of Vegetation Feature Based on Two-dimensional Wavelet Transformation[J].Remote Sensing Technology and Application,2003,18(5):317-320.[徐丽华,岳文泽.基于二维小波变换的遥感分类研究[J].遥感技术与应用,2003,18(5):317-320.]
[12]Wang Qi,Li Xingchao,Li Junjie,et al.Evaluation on Fusion of CBERS-02B CCD and HR Images[J].Remote Sensing Technology and Application,2008,23(4):467-470.[王奇,李杏朝,李俊杰,等.CBERS-02B星HR与CCD影像融合研究[J].遥感技术与应用,2008,23(4):467-470.]
[13]Yao Min.Digital Image Processing[M].Beijing:Machinery Industry Press,2006,199-200.[姚敏.数字影像处理[M].北京:机械工业出版社,2006,199-200.]
[14]Wang Jian,Zhang Jixian.Image Merger Based on Wavelet Transform Theory and Its Evaluation[J].Remote Sensing Information,2006,17-19.[王坚,张继贤.基于小波变换理论的影像融合及评价[J].遥感信息,2006,17-19.]
[1] 李佳佳,束进芳,裘增欢,符冉迪,金炜. 面向滨海湿地的全色/多光谱影像融合方法与应用分析——以杭州湾(1999~2018年)为例[J]. 遥感技术与应用, 2021, 36(3): 627-637.
[2] 杨昊翔,张丽,闫敏,林光辉. 基于高时空分辨率融合影像的红树林总初级生产力遥感估算[J]. 遥感技术与应用, 2021, 36(2): 453-462.
[3] 乔海伟,张彦丽. 融合FY-3C号和FY-4A号卫星数据的积雪面积变化研究—以祁连山区为例[J]. 遥感技术与应用, 2020, 35(6): 1320-1328.
[4] 崔先亮,陈立福,邢学敏,袁志辉. 基于频带特征融合的GL-CNN遥感图像场景分类[J]. 遥感技术与应用, 2019, 34(4): 712-719.
[5] 梁丽娟, 黄万里张容焱, 林广发, 彭俊超, 梁春阳. Sentinel-2卫星影像融合方法与质量评价分析[J]. 遥感技术与应用, 2019, 34(3): 612-621.
[6] 杨朦朦,汪汇兵,欧阳斯达,范奎奎,戚凯丽. 基于双树复小波分解的BP神经网络遥感影像分类[J]. 遥感技术与应用, 2018, 33(2): 313-320.
[7] 周为峰,曹利,李小恕,程田飞. 沿海牡蛎养殖的WorldView-2影像融合方法评价[J]. 遥感技术与应用, 2018, 33(1): 103-109.
[8] 张霞,孙伟超,帅通,孙艳丽. 基于小波变换的图像条带噪声去除方法[J]. 遥感技术与应用, 2015, 30(6): 1168-1175.
[9] 邓琳,邓明镜,张力树. 高分辨率遥感影像阴影检测与补偿方法优化[J]. 遥感技术与应用, 2015, 30(2): 277-284.
[10] 万智萍. 结合方向小波的多光谱与全色遥感图像融合算法[J]. 遥感技术与应用, 2014, 29(4): 660-668.
[11] 胡洋,习晓环,王成,肖勇. Pléiades卫星影像融合方法与质量评价[J]. 遥感技术与应用, 2014, 29(3): 476-481.
[12] 张宁丽,范湘涛,朱俊杰. 面向亚像元级积雪信息提取的MODIS影像波段融合方法研究[J]. 遥感技术与应用, 2013, 28(4): 610-617.
[13] 汤益先,赫永杰,张红,王超. 基于FFT平移与相关分析的多尺度星载SAR自动配准[J]. 遥感技术与应用, 2013, 28(4): 618-626.
[14] 郑中,祁元,张金龙. 基于光谱角和光谱距离评价指标的遥感影像融合方法比较研究——以QuickBird数据为例[J]. 遥感技术与应用, 2013, 28(3): 437-443.
[15] 刘 辉,谢天文. 基于PCA与HIS模型的高分辨率遥感影像阴影检测研究[J]. 遥感技术与应用, 2013, 28(1): 78-84.