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基于经验模态分解的高分辨率影像融合(英文)
引用本文:王坚,张继贤,刘正军.基于经验模态分解的高分辨率影像融合(英文)[J].地球空间信息科学学报,2008,11(1):31-37.
作者姓名:王坚  张继贤  刘正军
作者单位:School of Environment and Spatial Informatics China University of Mining and Technology,South Jiefang Road Xuzhou 221008 China,Institute of Photogrammetry and Remote Sensing Chinese Academy of Surveying and Mapping 16 Beitaiping Road Beijing 100039 China.
摘    要:High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition (EMD). The intensity hue saturation (IHS) transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function (IMF) for the merger on the basis of EMD analysis on specific row (column) pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms (wavelet, IHS, Brovey). The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.

关 键 词:经验模态分解  高分辨率  影像融合  遥感技术

EMD based multi-scale model for high resolution image fusion
Jian Wang,Jixian Zhang,Zhengjun Liu.EMD based multi-scale model for high resolution image fusion[J].Geo-Spatial Information Science,2008,11(1):31-37.
Authors:Jian Wang  Jixian Zhang  Zhengjun Liu
Institution:(1) School of Environment and Spatial Informatics, China University of Mining and Technology, South Jiefang Road, Xuzhou, 221008, China;(2) Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, 16 Beitaiping Road, Beijing, 100039, China
Abstract:High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition (EMD) . The intensity hue saturation (IHS) transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function (IMF) for the merger on the basis of EMD analysis on specific row (column ) pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms (wavelet, IHS, Brovey). The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.
Keywords:image fusion  experimental model decomposition  quantitatively evaluation
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