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CBERS-02B星数据融合方法评价 被引量:5

DATA FUSION EVALUATION OF CBERS-02B
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摘要 CBERS-02B星(以下简称02B星)多光谱CCD数据与全色HR数据空间分辨率相差较大,给图像融合带来一定困难。在对IHS变换、主成分变换、Brovey变换及GS变换等融合算法分析的基础上,利用02B星数据进行了融合试验。通过对试验结果的目视评价与定量分析发现,主成分变换和GS变换方法融合图像纹理信息较清晰,光谱保真度较好。在GS变换融合中,可利用02B星CCD相机第5波段模拟GS变换的低分辨率输入,融合结果统计值优于PC变换。 CBERS - 02B multi - spectral CCD data are considerably different from HR panchromatic data in resolution, which causes great difficulty in image fusion. Based on an analysis of such means as the IHS transform fusion method, the principal component transform fusion method, the Brovey transform fusion method and the GS transform integration algorithm, the authors tested the fusion methods on CBERS -02B data. The evaluation of the visual and quantitative analysis of the results reveals that the PC and GS transform fusion image texture information is fairly clear and has better spectral fidelity. In the GS transformation fusion, Band 5 of the CBERS - 02B CCD camera can he used as the low - resolution analog input, and the result of the statistical value is better than that of the PC transform.
出处 《国土资源遥感》 CSCD 2009年第1期64-68,共5页 Remote Sensing for Land & Resources
基金 "资源一号卫星02B星数据模拟与国土资源应用评估"及中国地质调查局项目"中巴02B星遥感数据应用与数据共享"科研项目共同资助
关键词 CBERS-02B星 图像融合 主成分变换融合 GS变换融合 CBERS -02B satellite Image fusion Principal component transform fusion GS transform fusion
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参考文献13

  • 1Campbell J B. Introduction to Remote Sensing, Third Edition[ M]. New York: The Guilford Press, 2002.
  • 2Garzelli A. Possibilities and Limitations of the Use of Wavelets in Image Fusion [ C ]. IEEE, 2002,66 - 88.
  • 3JohnR.Jensen,著.陈晓玲,等,译.遥感数字影像处理导论[M].北京:机械工业出版社,2007.
  • 4Pohl C, van Genderen J L . Muhisensor Image Fusion in Remote Sensing: Concepts, Methods and Applications [ J ]. International Journal of Remote Sensing, 1998, 19 (5) : 823 - 854.
  • 5Rafael C Gonzalez, Richard E. Woods Digital Image Processing (Second Edition) [M]. Beijing: Publishing House of Electronics Industry, 2003.
  • 6李存军,刘良云,王纪华,王人潮.两种高保真遥感影像融合方法比较[J].中国图象图形学报(A辑),2004,9(11):1376-1385. 被引量:97
  • 7Chena C M, Hepnerb G F, Forsterb R R. Fusion of Hyperspectral and Radar Data Using the IHS Transformation to Enhance Urban Surface Features[ J]. Photogrammetry & Remote Sensing,2003,58 :19 - 30.
  • 8Su Y, Huang P S, Lin C F, et al. Target Cluster Fusion Approach for Classifying High Resolution IKONOS Imagery [ J 1. Vision, Image and Signal Processing, 2004,151 (4) :241 -249.
  • 9王建梅,李德仁.QuickBird全色与多光谱数据融合方法用于土地覆盖分类中的比较研究[J].测绘通报,2005(10):37-40. 被引量:32
  • 10孙家柄.遥感原理与应用[M].武汉:武汉大学出版社,2003.220-281.

二级参考文献17

  • 1北京大学数学系.高等代数(第二版)[M].北京:高等教育出版社,1988..
  • 2LE M J, COLE R A, EASTMAN R, et al. Multiple Sensor Image Registration, Image Fusion and Dimension Reduction of Earth Science Imagery [ A ]. Information Fusion, Proceedings of the Fifth International Conference[C]. [s.l. ]: [s.n. ], 2002.
  • 3SU Y, HUANG P S, LIN C F, et al. Target-cluster Fusion Approach for Classifying High Resolution IKONOS Imagery[J]. Vision, Image and Signal Processing, 2004,151 (4) : 241-249.
  • 4DAVIS C H, WANG X Y. Urban Land Cover Classification from High Resolution Multi-spectral IKONOS Imagery[A]. Geoscience and Remote Sensing Symposium[C]. [s.l. ]: [s. n. ] ,2002.
  • 5WEBER C, RANCHIN T, PUISSANT A, et al. Extraction of Urban Features in Strasbourg, France: Comparison of Two Fusion Algorithms for Quickbird MS and Pan Data[A]. Remote Sensing and Data Fusion over Urban Areas[C]. [s.l. ]: [s. n. ], 2003.206-210.
  • 6LIU J G. Smoothing filter-based intensity modulation: a spectral preserve image fusion technique for improving spatial details[J].International Journal of Remote Sensing, 2000,21(18) :3461-3472.
  • 7Carper W J, Lillesand T M, Kiefer R W. The use of intensityhue-saturation transformations for merging spot panchromatic and multispeetral image data[J]. Photogrammetrie Engineeringand Remote Sensing, 1990,52(10):1637-1646.
  • 8Chavez P S, Sides S C, Anderson J A. Comparison of three different methods to merge multiresolution and multispeetral data: landsat tm and spot panchromatic [J]. Photogrammetrie Engineering and Remote Sensing, 1991,57(3): 295-303.
  • 9Clayton D G. Gram-Schmidt orthogonalization [J]. Applied Statistics, 1971,20(3) : 335- 338.
  • 10Laben. Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening [P]. US Patent:6 011 875, Jan,4, 2000.

共引文献213

同被引文献41

  • 1宋杨,万幼川.一种自适应的基于局部小波系数特征的遥感图像融合方法[J].遥感信息,2007,29(1):3-6. 被引量:6
  • 2阎秀英,蔡伟.中巴地球资源卫星产品的推广应用与市场展望[C].中巴地球资源卫星应用研究论文集,2003:41-47.
  • 3孙家柄,舒宁,关泽群.遥感原理、方法和应用[M].北京:测绘出版社,1997:1-46.
  • 4贾永红,李均力.选择最佳波段组合的方法研究[A].第十四届全国遥感技术学术交流会论文摘要集,2003.
  • 5Campbell J B. Introduction to Remote Sensing, Third Edition[M]. New York:The Guilford Press,2002.
  • 6Clayton D G. Gram Schrnidt Orthogonallization[J].Applied Stat- istics, 1971,20(3):335-338.
  • 7Campbell J B. Introduction to remote sensing[M].New York The.Guilford Press,2002.
  • 8赵英时.遥感应用分析原理与方法[M]北京:科学出版社,2003.
  • 9崔铁军.地理空间数据库原理[M]北京:科学出版社,2007.
  • 10泮雪芹,钱乐祥,宫少燕.遥感影像数据融合方法的比较和分析——以开封地区SPOT影像数据为例[J].南京师大学报(自然科学版),2007,30(4):99-103. 被引量:5

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