Abstract
In this work, we propose redundant discrete wavelet transform (RDWT) based fusion for multimodal medical images. The shift invariance nature of RDWT shows its usefulness for fusion. The proposed method uses maximum scheme for fusion of medical images. We have experimented with several sets of medical images and shown results for three sets of medical images. The effectiveness of fusion results has been shown using edge strength, and mutual information fusion metrics. The qualitative and quantitative comparison of the proposed method with spatial domain fusion methods (Linear, Sharp, and principal component analysis (PCA)) and wavelet domain fusion methods (discrete wavelet transform (DWT), lifting wavelet transform (LWT), and multiwavelet transform (MWT)) proves the superiority of the proposed fusion method.
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References
Dasarathy, B.V.: Information fusion in the realm of medical applications – A bibliographic glimpse at its growing appeal. Information Fusion 13(1), 1–9 (2012)
Singh, R., Khare, A.: Fusion of multimodal medical images using Daubechies complex wavelet transform- A multiresolution approach. Information fusion (Article in Press), http://dx.doi.org/10.1016/j.inffus.2012.09.005
Singh, R., Srivastava, R., Prakash, O., Khare, A.: Multimodal medical image fusion in dual tree complex wavelet domain using maximum and average fusion rules. Journal of Medical Imaging and Health Informatics 2(2), 168–173 (2012)
Rockinger, O., Fechner, T.: Pixel level fusion: the case of image sequences. In: Signal Processing, Sensor Fusion, and Target Tracking (SPIE), vol. 3374, pp. 378–388 (1998)
Clevers, J.G.P.W., Zurita-Milla, R.: Multisensor and multiresolution image fusion using the linear mixing model. In: Stathaki, T. (ed.) Image Fusion: Algorithms and Applications, pp. 67–84. Academic Press, Elsevier (2008)
Tian, J., Chen, L., Ma, L., Yu, W.: Multi-focus image fusion using a bilateral gradient-based sharpness criterion. Optics Communications 284(1), 80–87 (2011)
Naidu, V.P.S., Raol, J.R.: Pixel-level image fusion using wavelets and principal component analysis. Defence Science Journal 58(3), 338–352 (2008)
Hamza, A.B., He, Y., Krim, H., Willsky, A.: A multiscale approach to pixel-level image fusion. Integrated Computer-Aided Engineering 12(2), 135–146 (2005)
Li, H., Manjunath, B.S., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing 57(3), 235–245 (1995)
Cheng, S., He, J., Lv, Z.: Medical images of PET/CT weighted fusion based on wavelet transform. In: The Second International Conference on Bioinformatics and Biomedical Engineering (ICBBE), pp. 2523–2525 (2008)
Kor, S., Tiwary, U.S.: Feature level fusion of multimodal medical images in lifting wavelet transform domain. In: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2004), vol. 1, pp. 1479–1482 (2004)
Liu, Y., Yang, J., Sun, J.: PET/CT medical image fusion algorithm based on multiwavelet transform. In: Second International Conference on Advanced Computer Control (ICACC), vol. 2, pp. 264–268 (2010)
Zhang, Q., Wang, L., Li, H., Ma, Z.: Similarity-based multimodality image fusion with shiftable complex directional pyramid. Pattern Recognition Letters 32(13), 1544–1553 (2011)
Singh, R., Khare, A.: Multimodal medical image fusion using Daubechies complex wavelet transform. In: Proceedings of IEEE International Conference on Information and Communication Technology (ICT 2013I), Kanyakumari, India, pp. 869–873 (2013)
Fowler, J.: The redundant discrete wavelet transform and additive noise. IEEE Signal Processing Letters 12(9), 629–632 (2005)
Singh, R., Vatsa, M., Noore, A.: Multimodal Medical Medical Image Fusion using Redundant Wavelet Transform. In: Proceedings of Seventh International Conference on Advances in Pattern Recognition, pp. 232–235 (2009)
Yockey, D.A.: Artifacts in wavelet merging. Optical Engineering 35(7), 2094–2101 (1996)
Stathaki, T. (ed.): Image Fusion Algorithms and Applications. Elsevier (2011)
Adam, I.: Complex wavelet transform: application to denoising. PhD Thesis, Politehnica University of Timisoara Universite DE RENNES (2010), http://www.tc.etc.upt.ro/docs/cercetare//teze_doctorat/tezaFiroiu.pdf
Li, S., Yang, B., Hu, J.: Performance comparison of different multi-resolution transforms for image fusion. Information Fusion 12(2), 74–84 (2011)
Singh, R., Khare, A.: Objective evaluation of noisy multimodal medical image fusion using Daubechies complex wavelet transform. In: Proceedings of the 8th Indian Conference on Vision, Graphics and Image Processing (ICVGIP-12). IIT Mumbai, India (2012), http://dx.doi.org/10.1145/2425333.2425405
Guihong, Q., Dali, Z., Pingfan, Y.: Information Measure for Performance of Image Fusion. Electronics Letters 38(7), 313–315 (2002)
Xydeas, S., Petrovic, V.: Objective Image Fusion Performance Measure. Electronics Letters 36(4), 308–309 (2000)
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Singh, R., Khare, A. (2014). Redundant Discrete Wavelet Transform Based Medical Image Fusion. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_44
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DOI: https://doi.org/10.1007/978-3-319-04960-1_44
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