期刊文献+

基于区域特性选择的遥感图像融合方法 被引量:7

Fusion of Remote Sensing Images Using Region-based Selection Operator
在线阅读 下载PDF
导出
摘要 提出了一种新的遥感图像融合方法,其基本思想是首先对多光谱遥感图像(MS)进行IHS变换得到IHS色彩空间的I、H、S分量;然后将高分辨率全色图像和MS的I分量进行3层小波变换,并采取基于区域特性选择的融合算子对小波系数进行选择,然后经小波逆变换重构得到新的强度分量I;′最后将I′、H、S进行IHS逆变换得到融合后的图像。此外,文中引入了相关系数,相对平均光谱误差指数(RASE),相对整体维数综合误差(ERGAS)对融合图像的光谱质量进行评价,使用将融合图像与高分辨率全色图像分别经过拉普拉斯滤波器的滤波以提取细节信息,然后计算相关系数的方法对融合图像的空间细节质量进行评价。实验结果表明,本文算法在光谱质量的改善方面明显优于IHS及一些经典的小波变换遥感图像融合算法。 In this paper, a novel hierarchical image fusion scheme is presented. The main idea is to perform a intensityhue-saturation(IHS) transform of multispectral image( MS), then achieve 3 layers wavelet decomposition of the I weight of MS and Panchromatic image(PAN) , at the same time, adopt the fusion arithmetic operator of region selection and weighted average operator to select the wavelet coefficient. Thus the fused I weight(I') is got by taking inverse wavelet transform. Finally the fused image is obtained by inverse IHS transform of I' weight and the H, S weights of MS. In addition, this paper uses the correlation coefficient, relative average spectral error index (RASE), and relative global dimensional synthesis error(ERGAS) to evaluate the performance of the fusion image. The experimental results show that the fusion scheme put forward in this paper is better than IHS and some other classical fuse methods based on wavelet transform in improving spectrum quality of remote sensing image.
出处 《中国图象图形学报》 CSCD 北大核心 2007年第2期228-233,共6页 Journal of Image and Graphics
基金 国家自然科学基金项目(60374033) 江苏省自然科学基金项目(BK2002064) 江苏省高技术研究重大项目(BG2006003)
关键词 遥感图像融合 小波分解 IHS变换 区域特性选择 融合性能评价 fusion of remote sensing image, wavelet decomposition, IHS transform, region-based selection
  • 相关文献

参考文献7

  • 1Xiao Gang,Jing Zhong-liang,Li Jian-xun.Analysis of color distortion and improvement for IHS image fusion[A].In:The Proceeding of 2003 IEEE International Conference on Intelligent Transportation Systems[C],Shanghai,2003:80 - 85.
  • 2石爱业,徐立中,黄风辰.一种改进的基于小波变换的遥感图像融合方法[J].仪器仪表学报,2004,25(z1):690-691. 被引量:2
  • 3刘贵喜,杨万海.基于小波分解的图像融合方法及性能评价[J].自动化学报,2002,28(6):927-934. 被引量:137
  • 4王文杰,唐娉,朱重光.一种基于小波变换的图象融合算法[J].中国图象图形学报(A辑),2001,6(11):1130-1135. 被引量:39
  • 5Burt P J,Kolczynski R J.Enhanced image capture through fusion[A].In:Proceedings of the Fourth International Conference on Computer Vision[C],Berlin,Germany,1993:173 - 182.
  • 6Maia Gonzalez-Audicana,Jose Luis Saleta,Raquel Garcia Catalan,et al.Fusion of multispectral and panchromatic images using improve IHS and PCA mergers based on wavelet decomposition[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42 (6):1291 - 1299.
  • 7Zhou J,Civco D L,Silander J A.A wavelet transforms method to merge Landsat TM and SPOT panchromatic data[J].International Journal of Remote Sense,1998,19(4):743 -757.

二级参考文献15

  • 1[1]Luo R C, Kay M G. Multisensor Integration And Fusion For Intelligent Machines And Systems. New Jersey: Ablex Publishing Corporation, 1995. 1~25
  • 2[2]Varshney P K. Multisensor data fusion. Electronics & Communication Engineering Journal, 1997,9(6):245~253
  • 3[3]Yocky D A. Image merging and data fusion by means of the discrete two-dimensional wavelet transform. Journal of Optical Society of America, 1995, 12(9):1834~1841
  • 4[4]Nunez J, Otazu X, Fors O, Prades A, Pala V, Arbiol R. Multiresolution-based image fusion with additive wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 1999,37(3):1204~1211
  • 5[5]Mallat S G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989,11(7):674~693
  • 6[6]Mallat S G. A Wavelet Tour of Signal Processing. San Diego: Academic Press, 1998.302~310
  • 7[7]Campbell F W, Robson J. Application of Fourier analysis to the visibility of gratings. Journal of Physiology, 1968,197:551~556
  • 8[1]Chavez P S, Sides S C, Anderson J A. Comparison of three different method to merge multiresolution and multispectral data,Landsat TM and SPOT panchromatic [J]. Photogrammetric Engineering & Remote Sensing,1991,57 (3) :295~303.
  • 9[2]Shettigara V K. A Generalized component substitution technique for spatial enhancement of multispectral images using a higher resolution data set[J]. Photogrammetric Engineering & Remote Sensing, 1992,58: 561 ~567.
  • 10[4]Nunez J,Otazu X,Fors O. Multiresolution-based image fusion with additive wavelet decomposition [J]. IEEE Trans. Geoscience and Remote Sensing, 1999, 37 (3):1204~1211.

共引文献175

同被引文献85

引证文献7

二级引证文献49

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部