Multisensor video fusion based on higher order singular value decomposition

Hu, 2004, A survey on visual surveillance of object motion and behaviors, IEEE Trans. Syst. Man Cybern. – Part C: Appl. Rev., 34, 334, 10.1109/TSMCC.2004.829274 Denman, 2010, Multi-spectral fusion for surveillance systems, Comput. Electric. Eng., 36, 643, 10.1016/j.compeleceng.2008.11.011 Snidaro, 2012, Fusing multiple video sensors for surveillance, ACM Trans. Multimedia Comput. Commun. Appl., 8, 7:1, 10.1145/2071396.2071403 Shi, 2014, Change detection in synthetic aperture radar images based on fuzzy active contour models and genetic algorithms, Math. Prob. Eng., 2014, 870936:1, 10.1155/2014/870936 Snidaro, 2007, Quality-based fusion of multiple video sensor for video surveillance, IEEE Trans. Syst. Man Cybern. – Part B: Cybern., 37, 1044, 10.1109/TSMCB.2007.895331 Lewis, 2007, Pixel- and region-based image fusion with complex wavelets, Inform. Fus., 8, 119, 10.1016/j.inffus.2005.09.006 Li, 2011, Performance comparison of different multi-resolution transforms for image fusion, Inform. Fus., 12, 74, 10.1016/j.inffus.2010.03.002 Zhang, 2013, Multimodality image fusion by using both phase and magnitude information, Pattern Recogn. Lett., 34, 185, 10.1016/j.patrec.2012.09.020 O. Rockinger, Image sequence fusion using a shift-invariant wavelet transform, in: Proceedings of the International Conference on Image Processing, 1997, pp. 288–291. Bennett, 2007, Multispectral bilateral video fusion, IEEE Trans. Image Process., 16, 1185, 10.1109/TIP.2007.894236 Zhang, 2012, A novel video fusion framework using surfacelet transform, Opt. Commun., 285, 3032, 10.1016/j.optcom.2012.02.064 Zhang, 2013, Multisensor video fusion based on spatial–temporal salience detection, Signal Process., 93, 2483, 10.1016/j.sigpro.2013.03.018 Xu, 2014, Image sequence fusion and denoising based on 3D shearlet transform, J. Appl. Math., 2014, 652128:1, 10.1155/2014/652128 Lu, 2007, Multidimensional directional filter banks and surfacelets, IEEE Trans. Image Process., 16, 918, 10.1109/TIP.2007.891785 Ngyuen, 2010, Uniform discrete curvelet transform, IEEE Trans. Signal Process., 58, 3618, 10.1109/TSP.2010.2047666 Negi, 2012, 3D discrete shearlet transform and video processing, IEEE Trans. Image Process., 21, 2944, 10.1109/TIP.2012.2183883 Paul, 2013, Video search and indexing with reinforcement agent for interactive multimedia services, ACM Trans. Embedded Comput. Syst., 12, 25:1, 10.1145/2423636.2423643 Wang, 2012, Novel spatio-temporal structural information based video quality metric, IEEE Trans. Circuits Syst. Video Technol., 22, 989, 10.1109/TCSVT.2012.2186745 Bergqvist, 2010, The higher-order singular value decomposition: theory and application, IEEE Signal Process. Mag., 27, 151, 10.1109/MSP.2010.936030 Lathauwer, 2000, A multilinear singular value decomposition, SIAM J. Matrix Anal. Appl., 21, 1253, 10.1137/S0895479896305696 Tucker, 1966, Some mathematical notes on three-mode factor analysis, Psychometrika, 31, 279, 10.1007/BF02289464 Rajwade, 2013, Image denoising using the higher order singular value decomposition, IEEE Trans. Pattern Anal. Mach. Intell., 35, 849, 10.1109/TPAMI.2012.140 Wang, 2011, A novel face recognition method based on sub-pattern and tensor, Neurocomputing, 74, 3553, 10.1016/j.neucom.2011.06.017 Constantini, 2008, Higher order SVD analysis for dynamic texture synthesis, IEEE Trans. Image Process., 17, 42, 10.1109/TIP.2007.910956 Thomason, 2011, Higher order singular value decomposition of tensors for fusion of registered images, J. Electron. Imaging, 20, 013023:1, 10.1117/1.3563592 Liang, 2012, Image fusion using higher order singular value decomposition, IEEE Trans. Image Process., 21, 2898, 10.1109/TIP.2012.2183140 Kolda, 2009, Tensor decompositions and applications, SIAM Rev., 51, 455, 10.1137/07070111X T.G. Kolda, Multilinear Operators for Higher-order Decompositions, Technical Report Number SAND 2006-2081, Sandia National Laboratories, Albuquerque, New Mexico and Livermore, California, April 2006. Wu, 2010, Morphological dilation image coding with context weights prediction, Signal Process.: Image Commun., 25, 717 T. Zaveri, M. Zaveri, A novel hybrid pansharpening method using contourlet transform, in: Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence, 2009, pp. 363–368. Zhang, 2011, Similarity-based multimodality image fusion with shiftable complex directional pyramid, Pattern Recogn. Lett., 32, 1544, 10.1016/j.patrec.2011.06.002 Wang, 2002, A universal image quality index, IEEE Signal Process. Lett., 9, 81, 10.1109/97.995823 G. Piella, New quality measures for image fusion, in: Proceedings of the 7th International Conference on Information Fusion, 2004, pp. 542–546. Zhang, 2012, Video fusion performance evaluation based on structural similarity and human visual perception, Signal Process., 92, 912, 10.1016/j.sigpro.2011.10.004 V. Petrovic, T. Cootes, R. Pavlovic, Dynamic image fusion performance evaluation, in: Proceedings of the IEEE International Conference on Information Fusion, 2007, pp. 1–7. Chou, 2011, Robust automatic rodent brain extraction using 3-D pulse-coupled neural networks (PCNN), IEEE Trans. Image Process., 20, 2554, 10.1109/TIP.2011.2126587 Gastal, 2011, Domain transform for edge-aware image and video processing, ACM Trans. Graph., 30, 69:1, 10.1145/2010324.1964964 Loza, 2010, Non-Gaussian model-based fusion of noisy images in the wavelet domain, Comput. Vis. Image Underst., 114, 54, 10.1016/j.cviu.2009.09.002 Do, 2005, The contourlet transform: an efficient directional multiresolution image representation, IEEE Trans. Image Process., 14, 2091, 10.1109/TIP.2005.859376