Fusion of Panchromatic and Multispectral Images Based on the Second Generation Bandelet

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In order to gain a new image with high spatial resolution and abundant spectrum by fusing panchromatic and multispectral images, a novel fusion algorithm based on the generation Bandelet is presented, and the fusion rule of Bandelet coefficients reposes on maximum absolute value of frequence. Fusion experiments based on new method, IHS and wavelet transform are carried out with panchromatic and multispectral images of Landsat-7. The experimental results show that fused image of new method is more excellent. Image edges are more distinct, and prove that Bandelet transform has the character of tracking image edges adaptively.

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478-481

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July 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Bin Hou, Weifeng Qiao, Zaihong Sun (2006) Remote-Sensing Image Fusion Based on HIS Transform and àtrous Wavelet Decomposition. Journal of Nanjing Normal University(Natural Science), 29: 116-220

Google Scholar

[2] Lei Guo, Huihui Li, Yongsheng Bao (2008) Image Fusion. Beijing: Electronic Industry Press

Google Scholar

[3] Peyré G, Mallat S (2005) Discrete bandelets with geometri orthogonal filters. IEEE International Conference on Image Processing, Vancouver, 65-68

DOI: 10.1109/icip.2005.1529688

Google Scholar

[4] Jingwen Yan, xiaobo Qu (2008) Analysis and Application Beyond Wavelet. Beijing: National Defence Industry Press

Google Scholar

[5] Xiaobo Qu, Jinwen Yan, Guofu Xie, et al (2007) A novel image fusion algorithm based on bandelet transform. Chinese Optics Letters, 569-572.

Google Scholar

[6] Licheng Jiao, Biao Hou, Shuang Wang, et al (2008) Image Multiscale Geometric Analysis: Theory and Application. Xi'an: Xi'an Electronic Science and Technology University Press

Google Scholar

[7] Liangpei Zhang, Lifu Zhang (2005) Hyperspectral Remote Sensing. Wuhan: Wuhan University Press

Google Scholar

[8] SHAW G, MANKOLAKIS D. Signal processing for hyperspectral spectral image exploitation. IEEE Signal Processing Magazine, (2002)19: 12-l6

DOI: 10.1109/79.974715

Google Scholar

[9] Donoho D L (1999) Wedgelets: Nearly-Minimax Estimation of Edges. Annals of Stat, 859-897

DOI: 10.1214/aos/1018031261

Google Scholar

[10] Ruihua Liang, Lizhi Cheng, zhicheng Zhu (2007) Image Coding Based on Second Generation Bandelet Transform. Modern Electronics Technique, 4: 61-65

Google Scholar

[11] E.L. Pennec, S.Mallat (2005) Sparse Geometrie Image Representation with bandelets. IEEE Trans. on Image Processing. 423-438

DOI: 10.1109/tip.2005.843753

Google Scholar

[12] Yi Long (2008) The Application of Bandelet Transform in Image Denoise and Enhancement processing. Chengdu: Southwest Jiaotong University

Google Scholar