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Hybrid Fusion Technique Using Dual Tree Complex Wavelet Transform for Satellite Remote Sensor Images


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DOI: https://doi.org/10.15866/irecos.v9i9.3003

Abstract


Image Fusion is the process of merging two or more images to form a single image which has all the details of the individual images. This technique is used in satellite remote sensor images to fuse high resolution panchromatic image with the low resolution multispectral image to form a single high resolution multispectral image. Among the existing fusion techniques, wavelet based methods have proved to produce improved results. The key objective of this paper is to introduce a new hybrid fusion method to fuse PAN image and MS image by using Dual Tree complex wavelet transform (DTCWT) and IHS technique. Firstly the limitations of classical Discrete Wavelet Transform (DWT) are explained in brief. Secondly the key properties of complex wavelets and its theory are described followed by proposing a new fusion method using complex wavelets. Finally experimental results are evaluated using quality assessment metrics which shows that the proposed method performs remarkably better than the classical DWT method.
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Keywords


Complex Wavelet Transform; IHS Method; Image Fusion; Remote Sensing

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References


Edwards and P.A.Davis, “The use of Intensity-Hue-Saturation transformation for producing color shaded-relief images,” Photogramm. Eng. Remote Sens., vol. 60, no. 11, pp. 1369–1374, 1994.

Ivan W. Selesnick, Richard G. Baraniuk, and Nick G. Kingsbury “The Dual –Tree complex wavelet transform,” IEEE signal processing magazine, pp.123-151, 2005.
http://dx.doi.org/10.1109/msp.2005.1550194

P. D. Shukla, “Complex wavelet transforms and their applications”, PhD Thesis, The University of Strathclyde, 2003.

Peter de Rivaz and Nick Kingsbury, “Bayesian image deconvolution and denoising using complex wavelets”, Proc. IEEE Conf. on Image Processing, Greece, paper 2639, 2001.
http://dx.doi.org/10.1109/icip.2001.958477

N.G. Kingsbury, “Image processing with complex wavelets,” Philos. Trans. R.Soc. London A, Math. Phys. Sci., vol. 357, no. 1760, pp. 2543–2560, 1999.
http://dx.doi.org/10.1098/rsta.1999.0447

Fernandes, “Directional, shift-insensitive, complex wavelet transforms with controllable redundancy”, PhD Thesis, Rice University, 2002.

Nick Kingsbury, “The dual_tree complex wavelet transform: A new efficient tool for image restoration and enhancement”, Proc. European Signal Processing Conference, EUSIPCO 98, Rhodes, pp. 319-322, 1998.

Wenbo W, Y.Jing, and K. Tingjun , “Study Of Remote Sensing Image Fusion And Its Application In Image Classification” The Int. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing ,Vol. XXXVI, Part B7, pp. 1141-1146, 2008.

S G Mallat, “A theory for multiresolution signal decomposition: The wavelet representation”, IEEE Trans. PAMI, 11(7), pp. 674-693, 1989.
http://dx.doi.org/10.1109/34.192463

Chibani, Y., and A. Houacine, “The joint use of the HIS Transform and the redundant wavelet decomposition for fusing multispectral and panchromatic images”, International Journal of Remote Sensing, 23(18), pp. 3821–3833, 2002.
http://dx.doi.org/10.1080/01431160110107626

J.G.Liu, “Smoothing filter-based intensity modulation:A spectral preserve image fusion technique for improving spatial details,” Int. J. Remote Sens., vol. 21, no. 18, pp. 3461–3472, 2000.
http://dx.doi.org/10.1080/014311600750037499

T.M.Tu, S.C.Su, H.C.Shyu, and P.S.Huang, “A new look at IHS-like image fusion methods,” Inf. Fusion, vol.2, no. 3, pp. 177–186, 2001.
http://dx.doi.org/10.1016/s1566-2535(01)00036-7

J. N´u˜nez, X. Otazu, O. Fors, A. Prades, V. c Pal`a, and R.Arbiol, “ Multiresolution-Based Image Fusion with Additive Wavelet Decomposition,” IEEE Transactions on Geoscience and Remote Sensing, vol.37, pp.1204 – 1211, 1999.
http://dx.doi.org/10.1109/36.763274

T. Ranchin and L. Wald, “Fusion of high spatial and spectral resolution images: The ARSIS concept and its implementation,” Photogramm. Eng. Remote Sens., vol. 66, no. 1, pp. 49–61, 2000.

B.Aiazzi, L.Alparone, S.Baronti, and A.Garzelli, “Context-driven fusion of high spatial and spectral resolution images based on over sampled multi-resolution analysis,” IEEE Trans. Geo sci. Remote Sens., vol. 40, no. 10, pp. 2300–2312, 2002.
http://dx.doi.org/10.1109/tgrs.2002.803623

Y. Zhang, “A new merging method and its spectral and spatial effects,” Int. J. Remote Sens., vol. 20, no. 10, pp. 2003–2014, 1999.
http://dx.doi.org/10.1080/014311699212317

Ehlers M., S. Klonusa, P. Johan and P. Rosso , “Multi-sensor image fusion for pansharpening in remote sensing”, International Journal of Image and Data Fusion, Vol. 1, No. 1, pp. 25–45, 2010.
http://dx.doi.org/10.1080/19479830903561985

R. A. Schowengerdt, Remote Sensing: Models and Methods for Image Processing (2nd ed. Orlando, FL: Academic, 1997).

Wang Z. and A.C. Bovik, “A universal image quality index,” IEEE Signal Process Lett., 9(3), pp. 81-84, 2002.
http://dx.doi.org/10.1109/97.995823

K.Shivsubramani, P soman, Krishnamoorthy, “Implementation and Comparative Study of Image Fusion Algorithms”, International Journal of Computer Applications (0975 – 8887) Volume 9, No.2, pp.3-6, 2010.
http://dx.doi.org/10.5120/1357-1832

Anjali Malviya and S.G.Bhirud,“Image Fusion of Digital Images”, Int. J. Recent Trends in Engineering, Vol.2, No.3, pp. 2-4, 2009.
http://dx.doi.org/10.1109/artcom.2009.235

V.P.S Naidu and J.R.Raol, “Pixel level Image fusion using wavelets and Principal component analysis”, Defence science Journal, Vol.58, No.3, pp. 338-352, 2008.

A. Goshtasby and S. G. Nikolov, “Image fusion: Advances in the state of the art”, Editorial- Science Direct, Special Issue on Image fusion, 8(2), pp. 114-118, 2007.
http://dx.doi.org/10.1016/j.inffus.2006.04.001

H.Wang, J. Peng, and W.Wu,” Fusion algorithm for multisensor image based on discrete multi wavelet transform,” IEEE Proc. Visual Image Signal Process., 149(5), 2002.
http://dx.doi.org/10.1049/ip-vis:20020612

K. Amolins, Y. Zhang, and P. Dare, “Wavelet based image fusion techniques - An introduction, review and comparison,” ISPRS Journal of Photogrammetry & Remote Sensing, vol.62, pp. 249–263, 2007.
http://dx.doi.org/10.1016/j.isprsjprs.2007.05.009

K. K. Gupta, R. Gupta, Wavelet Based Speckle Filtering of the SAR Images, (2006) International Review on Computers and Software (IRECOS), 1 (3), pp. 224-232.

Nougrara, Z., Benyettou, A., Abdellaoui, A., Bachari, N.I., Lahmar, K., Comparative study between two proposed methods of an extracted road network and its nodes from satellite images of Algeria sites for contribution to the elaboration of a geographical information system GIS, (2012) International Journal on Communications Antenna and Propagation (IRECAP), 2 (2), pp. 123-126.


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