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The Use of Complex Contourlet Transform on Fusion Scheme

Authors: Dipeng Chen, Qi Li


Image fusion aims to enhance the perception of a scene by combining important information captured by different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been thouroughly investigated for image fusion, since it takes advantages of approximate shift invariance and direction selectivity. But it can only handle limited direction information. To allow a more flexible directional expansion for images, we propose a novel fusion scheme, referred to as complex contourlet transform (CCT). It successfully incorporates directional filter banks (DFB) into DT-CWT. As a result it efficiently deal with images containing contours and textures, whereas it retains the property of shift invariance. Experimental results demonstrated that the method features high quality fusion performance and can facilitate many image processing applications.

Keywords: Complex contourlet transform, Complex wavelettransform, Fusion.

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[1] G. Piella, "A general framework for multi-resolution image fusion: from pixels to regions," PNA-R0211, ISSN 1386-3711, 2002.
[2] B. Jeon and D. A. Landrebe, "Decision fusion approach for multitemporal classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 7, pp. 1227-1233, 1999.
[3] R. K. Sharma and M. Pavel, "Adaptive and statistical image fusion," Society for information Display Digest of Technical Papers, vol. 27, pp. 969-972, 1996.
[4] M. N. Do and M. Vetterli, "Contourlets:A directional multi-resolution image representation", Proc. of IEEE intl. Conf. on Image Processing, Rochester, September 2002.
[5] M. N. Do and M. Vetterli, "Contourlets," Beyond Wavelets, Academic Press, New York, 2003.
[6] Z. Wang and A. C. Bovik, "A universal image quality index," IEEE Signal Processing Letters, vol. 9, no. 3, pp. 81-84, March 2002.
[7] Paul. R. Hill, C. N. Canagarajah, D. R. Bull, "Image fusion using complex wavelets". BMVC 2002.
[8] N. G. Kingsbury, "Shift invariant properties of the dual-tree complex wavelet transform," Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. ICASSP -99, March 1999.
[9] S. Sanjeevi, K. Vani and K. Lakshmi "Comparison of conventional and wavelet transform techniques for fusion of IRS-1C LISS-III and PAN Images," 22nd Asian Conference on Remote Sensing, Singapore, November 2001.
[10] A. R. Afary "Application of Wavelets Transform in Optimization of satellite Image Fusion", Master of Science Thesis, 2002.
[11] P. J. Burt and A. E. Adelson, "The Laplacian pyramid as a compact image code", IEEE Trans. on Communications, vol. 31, pp. 532-540, 1983.
[12] R. Eslami and H. Radha, "Wavelet-based contourlet transform and its application to image coding", IEEE intl. Conf. on Image Processing, 2004.
[13] L. Wald, T. Ranchin and M. Mangolini, "Fusion of Satellite images of difference spatial resolution: Assessing the quality of resulting images," Photogrammetric Engineering and Remote Sensing, vol. 63, no. 6, pp. 691-699, 1997.
[14] J. Li and Z. J. Liu, "Data fusion for remote sensing imagery based on feature," China Jounal of Remote Sensing, vol. 2, no. 2, pp. 103-107, 1998.
[15] W. Z. Shi, C. Q. Zhu, C. Y. Zhu and X. M. Yang, "Multi-Band wavelet for fusion SPOT Panchromatic and multispecteral images," Photogrammetric Engineering and Remote Sensing, vol. 69, no. 5, pp. 513-520, 2003.
[16] J. B. Sun, J. L. Liu and J. Li, "Multi-source remote sensing image data fusion," China Jounal of Remote Sensing, vol. 2, no. 1, pp. 47-50, 1998. S. M. Phoong, C. W. Kim, P. P. Vaidynathan, and R. Ansari, "A new class of two-channel biorthogonal filter banks and wavelet bases," IEEE Trans. Signal Proc., vol. 43, no. 3, pp. 649-665, March 1995.