| Technology and Methodology |
|
|
|
|
|
Remote sensing image fusion based on weighted filter empirical mode decomposition |
| LIANG Lingfei1, ZHANG Chong1, PING Ziliang2 |
1. School of Electronic & Information Engineering, Henan University of Science and Technology, Luoyang 471003, China;
2. School of Physics and Electronic Information, Inner Mongolia Normal University, Hohhot 010022, China |
|
|
|
|
Abstract Weighted filter empirical mode decomposition(WFEMD), as a new multi-scale and multi-resolution analysis algorithm, is more appropriate for the analysis of the image details than wavelet, super wavelet and dimensional empirical mode decomposition, and can solve the inherent defects of the traditional two-dimensional empirical mode decomposition(EMD). The main reason is that it directly computes the mean envelope by adaptive weighted mean filter. When WFEMD is introduced to the remote sensing image fusion, the characteristics of original images can be better extracted, and more information for fusion can be obtained. Firstly, the source images are decomposed by using WFEMD with the capability of acquirement of the high frequency data, the adaptability for some intrinsic mode functions (IMF) and the residual component, and then the IMFs and the residual component are fused with the details/background and average fusion regularity respectively at the corresponding scales. Finally, the fused IMFs and the residual component are reconstructed to obtain fusion results. Experiments have shown that the proposed algorithm is efficient in image fusion and is better than other current algorithms.
|
| Keywords
Guizhou
weak mineralization and alteration information
remote sensing information
contour map
distribution characteristic
|
|
|
|
Issue Date: 01 July 2014
|
|
|
[1] 吴艳,杨万海,李明.基于小波分解和进化策略的图像融合方法[J].光学学报,2003,23(6):671-676. Wu Y,Yang W H,Li M.Image fusion based on wavelet decomposition and evolutionary strategy[J].Acta Optica Sinica,2003,23(6):671-676.
[2] 董张玉,赵萍,刘殿伟,等.一种改进的小波变换融合方法及其效果评价[J].国土资源遥感,2012,24(3):44-49. Dong Z Y,Zhao P,Liu D W,et al.An improved wavelet transformation image fusion method and evaluation of its fusion result[J].Remote Sensing for Land and Resources,2012,24(3):44-49.
[3] 范文婷,傅平.一种基于小波变换的遥感图像融合方法[J].国土资源遥感,2008,20(3):24-26. Fan W T,Fu P.A remote sensing image fusion method on wavelet transform[J].Remote Sensing for Land and Resources,2008,20(3):24-26.
[4] 路雅宁,郭雷,李晖晖.结合边缘信息和图像特征信息的曲波域遥感图像融合[J].光子学报,2012,41(9):1118-1123. Lu Y N,Guo L,Li H H.Remote sensing image fusion using edge information and features of SAR image based on curvelet transform[J].Acta Photonica Sinica,2012,41(9):1118-1123.
[5] Huang N E,Shen Z,Long S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society,London A,1998,454(1971):903-995.
[6] Damerval C,Meignen S,Perrier V.A fast algorithm for bidimensional EMD[J].IEEE Signal Processing Letters,2005,12(10):701-704.
[7] Xu Y,Liu B,Liu J,et al.Two-dimensional empirical mode decomposition by finite elements[J].Proceedings of the Royal Society,London A,2006,462(2074):3081-3096.
[8] Xu G L,Wang X T,Xu X G.Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures[J].Pattern Recognition,2009,42(5):718-734.
[9] Wu Z H,Huang N E,Chen X Y.Multi-dimensional ensemble empirical mode decomposition[J].Advances in Adaptive Data Analysis,2009,1(3):339-372.
[10] Ahmed M U,Mandic D P.Image fusion based on fast and adaptive bidimensional empirical mode decomposition[C]//2010 13th Conference on Information Fusion.London,UK:IEEE Conference Proceedings,2010:1-6.
[11] Ohta Y I,Kanade T,Sakai T.Color information for region segmentation[J].Computer Graphic and Image Processing,1980,13(3):222-241.
[12] 高绍姝,金维其,王玲雪,等.图像融合质量客观评价方法[J].应用光学,2011,32(4):671-677. Gao S H,Jin W Q,Wang L X,et al.Objective quality assessment of image fusion[J].Journal of Applied Optics,2011,32(4):671-677. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
2014,
Vol. 26
