Vector Fusion of Multispectral Images Based on Multiwavelet Decomposition

Wu Xiao-rong; He Ming-yi; Zhang Yi-fan

doi:10.3724/SP.J.1146.2005.01127

Volume 29 Issue 4

Jan. 2011

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Zhang Shun, Gao Tie-Gang. Encryption Based on DNA Coding, Codon Grouping and Substitution[J]. Journal of Electronics & Information Technology, 2015, 37(1): 150-157. doi: 10.11999/JEIT140091

Citation:

Wu Xiao-rong, He Ming-yi, Zhang Yi-fan. Vector Fusion of Multispectral Images Based on Multiwavelet Decomposition[J]. Journal of Electronics & Information Technology, 2007, 29(4): 789-794. doi: 10.3724/SP.J.1146.2005.01127

Zhang Shun, Gao Tie-Gang. Encryption Based on DNA Coding, Codon Grouping and Substitution[J]. Journal of Electronics & Information Technology, 2015, 37(1): 150-157. doi: 10.11999/JEIT140091

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Vector Fusion of Multispectral Images Based on Multiwavelet Decomposition

doi: 10.3724/SP.J.1146.2005.01127

Received Date: 2005-09-06
Rev Recd Date: 2006-03-13
Publish Date: 2007-04-19

Abstract

Abstract

In the real domain, the finitely supported, orthogonal, symmetric nontrivial scalar wavelet bases do not exist, while the multiwavelet offers the finite support, symmetry, orthogonality simultaneously. As a result, the wavelet theory is extended to vector field. Considering vector characteristics provided by the coefficients of the multiwavelet transformed image, pixel-based and region-based scalar fusion schemes are extended to vector case and a novel fusion algorithm is also proposed in this paper. The new algorithm is based on vector fusion scheme in multiwavelet domain, which makes sufficient use of the correlation among the components of multiwavelet transform coefficient vectors to improve fusion quality. The original algorithm is carried out with emphases on the novelty of the fusion algorithm and the demonstration by using real multispectral image compared with algorithms employing wavelet scalar fusion scheme. The experimental results demonstrate that the proposed multiwavelet vector fusion algorithm can obtain both better subjective vision characteristics and better objective evaluation indices and outperform the wavelet scalar fusion scheme. Accordingly it is testified that when applied in image fusion, multiwavelet is more suitable than wavelet to human vision system and it is of great potential to wide applications.

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References(1)

References

[1] Ingrid Daubechies著，李建平，杨万年译. Ten Lectures on Wavelets. 北京：国防工业出版社，2004.5: 188~196, 239~245. [2] 成礼智，王红霞，罗永著. 小波的理论与应用.北京: 科学出版社, 2004.9, 第四章, 第五章. [3] 高西奇，甘露，邹采荣. 多小波变换的理论及其在图像处理中的应用. 通信学报, 1999, 20(11): 55~60. Gao Xi-qi, Gan Lu, and Zou Cai-rong. Multiwavelet: Theory and its applicationin image processing. Journal on Communications, 1999, 20(11): 55-60. [4] Chui Charles K and Lian Jian-ao. A study of orthonormal multiwavelets[J].Applied Numerical Mathematics.1996, 20(1):273-298 [5] Mallat Stephane G. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1989, 2(7): 674-693. [6] 张俊，佘二永，王润生. 平衡多小波在图像融合增强中的应用.计算机工程与科学, 2004, 26(1): 38-41. Zhang Jun, She Er-yong, and Wang Run-sheng. Balanced multiwavelet and its application in image fusion. Computer Engineering and Science, 2004, 26(1): 38-41. [7] Wang H, Peng J, and Wu W. Fusion algorithm for multisensor images based on discrete multiwavelet transform[J].IEE Proc.-Vis. Image Signal Process.2002, 149(5):283-289 [8] Wang Hai-hui. Multisensor image fusion by using discrete multiwavelet transform. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, 2004, vol.7: 4331-4336. [9] 王海晖，彭嘉雄. 基于多小波变换的图像融合研究.中国图像图形学报, 2004, 9(8): 1002~1007. [10] Strela Vasily, Heller Peter Niels, Strang Gilbert, Topiwala Pankaj, and Heil Christopher. The application of multiwavelet filter banks to image processing[J].IEEE Trans. on Image Processing.1999, 8(4):548-563 [11] Strela V. Multiwavelets: Theory and Application. [Ph.D. Thesis], MIT, 1996. [12] 程正兴，张玲玲. 多小波分析与应用. 工程数学学报，2001，18(1): 99-107. Cheng Zheng-xing, Zhang Ling-ling. Analysis of multiwavelet and application. Chinese Journal of Engineering Mathematics, 2001, 18(1): 99-107. [13] 黄卓君，马争鸣. 多小波图像编码中前置滤波器的设计. 电路与系统学报, 2000, 5(2): 62-66. Huang Zhuo-jun, Ma Zheng-ming. Prefilter design in multiwavelet image coding. Journal of Circuits and Systems, 2000, 5(2): 62-66. [14] 程云鹏. 矩阵论(第二版). 西安: 西北工业大学出版社，2001.6，第二章. [15] 徐飞，施晓红. MATLAB应用图像处理. 西安: 西安电子科技大学出版社，2002.5.

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