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DT-CWT Based Image Fusion Algorithm for Multi-Camera Imaging System

Hitesh Domadia, Vibha Gupta

Abstract


In this paper we proposed an Image Fusion Algorithm for Multi-Camera Imaging System. Image Fusion is a subfield of image processing which is a process of combining the relevant information from a set of images, into a single image,wherein the resultant fused image will be more informative and complete than any of the input images. A novel image fusion method is proposed in this thesis. In which multi camera images are fused. Multi-camera images are the same images captured by different camera. The focus of this paper is to develop a new algorithm to fuse a visual image and a corresponding IR image or CT AND MRI image for such a concealed weapon detection, and Medical application. The fused image obtained by the proposed algorithm will maintain the high resolution of the visual image incorporate any single image. The feasibility of the proposed fusion technique is tested and demonstrated by some experimental results in form of visual and mathematical output.


Keywords


DT-CWT, Filter Bank, Image Fusion, Multi-Camera Imaging

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References


A. M. Waxman, M. Aguilar, R. A. Baxter, D.A. Fay, D. B. Ireland, J. P. Racamato, W. D. Ross, Opponent-color fusion of multi-sensor imagery: visible, IR and SAR, Proceedings of IRIS Passive Sensors, vol.1, pp. 43-61, 1998.

Xiao Gang, Yang Bo, Jing Zhongliang. “Infrared and Visible Dynamic Image Sequence Fusion Based on Region Target Detection”, The 10th International Conference on Information Fusion. July 2007.

N.G. Kingsbury, “The dual-tree complex wavelet transform with improved orthogonality and symmetry properties”, IEEE

International Conference on Image Processing, pages 375–378, September 2000.

Kingsbury, N G (May 2001). "Complex wavelets for shift invariant analysis and filtering of signals" (PDF). Journal of Applied and Computational Harmonic Analysis 10 (3):234-253.

Selesnick, Ivan W.; Baraniuk, Richard G. and Kingsbury, Nick G. (November 2005). "The Dual-Tree Complex Wavelet Transform" (PDF).IEEE Signal Processing Magazine 22 (6): 123–151.

N. G. Kingsbury, "A dual-tree complex wavelet transform with improved orthogonality and symmetry properties", Proceedings of the IEEE Int. Conf. on Image Proc. (ICIP), 2000

N. G. Kingsbury. “Complex wavelets for shift invariant analysis and filtering of signals”, Journal of Applied and Computational Harmonic Analysis, Vol 10, No 3, pp 234-253, 2001.

I. W. Selesnick. “The design of approximate hilbert transform pairs of wavelet bases”, IEEE Trans. on Signal Process, 50(5): pp 1144-1152,2002.

M. Aguilar and J. R. New, Fusion of multi-modality volumetric medical imagery, ISIF 2002, pp. 1206-1212.

R. C. Gonzalez, R. E. Woods, Digital Image Processing, Second Edition,Prentice Hall, New Jersey 2002.

O. Rockinger. Image sequence fusion using a shift invariant wavelet transform. IEEE Transactions on Image Processing, 3:288–291, 1997.

Pankajkumar Mendapara, Aryaz Baradarani, Q.M. Jonathan Wu, “An Efficient Depth Map Estimation Technique Using Complex Wavelets”,ICME IEEE 2010

Shivsubramani Krishnamoorthy, K P Soman, “Implementation and Comparative Study of Image Fusion Algorithms”, International Journal of Computer Applications, Vol. 9, No. 2, pp. 25-35, Nov. 2010.

Prakash NK “Image Fusion based on biorthogonal wavelet”, International Journal of Enterprise Computing and Business Systems, Vol. 1 Issue 2, July 2011.

O. Rockinger. Image fusion toolbox for Matlab. Technical report, Metapix, 1999. http://www.metapix.de/toolbox.htm. 2, 3.2


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