Infrared and visible image fusion based on random projection and sparse representation

References

• Aharon, M., M. Elad, and A. M. Bruckstein. 2005. “K-SVD and its Non-Negative Variant for Dictionary Design.” Paper presented at the Optics & Photonics, San Diego, CA, July 31, 591411–591413.
   Google Scholar
• Baraniuk, R. G. 2007. “Compressive Sensing [Lecture Notes].” IEEE Signal Processing Magazine 24 (4): 118–121.
   Web of Science ®Google Scholar
• Candes, E. J., J. K. Romberg, and T. Tao. 2006. “Stable Signal Recovery from Incomplete and Inaccurate Measurements.” Communications on Pure and Applied Mathematics 59 (8): 1207–1223.
   Web of Science ®Google Scholar
• Davenport, M. A., M. F. Duarte, Y. C. Eldar, and G. Kutyniok. 2011. “Introduction to Compressed Sensing.” In Compressed Sensing: Theory and Applications, edited by Y. Eldar and G. Kutyniok. Cambridge University Press.
   Google Scholar
• Figueiredo, M. A. T., R. D. Nowak, and S. J. Wright. 2007. “Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems.” IEEE Journal of Selected Topics in Signal Processing 1 (4): 586–597.
   Web of Science ®Google Scholar
• Fu, M.-Y., and C. Zhao. 2009. “Fusion of Infrared and Visible Images Based on the Second Generation Curvelet Transform [j].” Journal of Infrared and Millimeter Waves 4: 003.
   Google Scholar
• Gan, Lu., T. Do, and T. D. Tran. 2008. “Fast Compressive Imaging Using Scrambled Block Hadamard Ensemble.” Paper presented at the 16th European signal processing conference, EUSIPCO 2008, Lausanne, August 25–29.
   Google Scholar
• Han, J., O. Loffeld, K. Hartmann, and R. Wang. 2010. “Multi Image Fusion Based on Compressive Sensing.” Paper presented at the 2010 international conference on audio, language and image processing, ICALIP 2010, Shanghai, November 23–25, 1463–1469.
   Google Scholar
• Jain, P., A. Tewari, and I. S. Dhillon. 2011. “Orthogonal Matching Pursuit with Replacement.” Advances in Neural Information Processing Systems 24: 1215–1223.
   Google Scholar
• Khajehnejad, M. A., X. Weiyu, A. S. Avestimehr, and B. Hassibi. 2011. “Analyzing Weighted L1 Minimization for Sparse Recovery with Nonuniform Sparse Models.” IEEE Transactions on Signal Processing 59 (5): 1985–2001. doi:10.1109/TSP.2011.2107904.
   Web of Science ®Google Scholar
• Li, X., and S.-Y. Qin. 2011. “Efficient Fusion for Infrared and Visible Images Based on Compressive Sensing Principle.” IET Image Processing 5 (2): 141–147.
   Web of Science ®Google Scholar
• Liu, G., and Y. Shen. 2012. “Ultrasonic Image Fusion Using Compressed Sensing.” Electronics Letters 48 (19): 1182–1184.
   Web of Science ®Google Scholar
• Liu, G. X., S. G. Zhao, and W. H. Yang. 2001. “Multi-Sensor Image Fusion Scheme Based on Gradient Pyramid Decomposition.” Journal of Optoelectronics – Laser 12: 293–296.
   Google Scholar
• Luo, X., J. Zhang, J. Yang, and Q. Dai. 2009. “Image Fusion in Compressed Sensing.” Paper presented at the 2009 IEEE international conference on image processing, ICIP 2009, Cairo, November 7–12, 2205–2208.
   Google Scholar
• Pajares, G., and J. Manuel de la Cruz. 2004. “A Wavelet-Based Image Fusion Tutorial.” Pattern Recognition 37 (9): 1855–1872.
   Web of Science ®Google Scholar
• Petrovi, V., and C. Xydeas. 2000. “On the Effects of Sensor Noise in Pixel-Level Image Fusion Performance.” Paper presented at the proceedings of the third international conference on information fusion, FUSION 2000, Vol. 12, Paris, July 10–13, 2:WEC3/14-WEC13/19.
   Google Scholar
• Qu, G., D. Zhang, and P. Yan. 2002. “Information Measure for Performance of Image Fusion.” Electronics Letters 38 (7): 313–315.
   Web of Science ®Google Scholar
• Sadjadi, F. 2005. “Comparative Image Fusion Analysis.” Paper presented at the IEEE computer society conference on computer vision and pattern recognition-workshops, CVPR workshops, Washington, DC , June 20–26.
   Google Scholar
• Wan, T., N. Canagarajah, and A. Achim. 2008. “Compressive Image Fusion.” Paper presented at the 2008 IEEE Iinternational conference on image processing, ICIP 2008, San Diego, CA, October 12–15, 1308–1311.
   Google Scholar
• Wan, T., and Z. Qin. 2010. “An Application of Compressive Sensing for Image Fusion.” Paper presented at the ACM International conference on image and video retrieval, ACM-CIVR 2010, Xi’an, July 5–7, 3–9.
   Google Scholar
• Wan, T., and Z. Qin. 2011. “An Application of Compressive Sensing for Image Fusion.” International Journal of Computer Mathematics 88 (18): 3915–3930.
   Web of Science ®Google Scholar
• Wang, H., J. Peng, and W. Wu. 2002. “Fusion Algorithm for Multisensor Images Based on Discrete Multiwavelet Transform.” Review of IEE Proceedings-Vision, Image and Signal Processing 149 (5): 283–289.
   Web of Science ®Google Scholar
• Yang, B., and S. Li. 2010. “Multifocus Image Fusion and Restoration with Sparse Representation.” IEEE Transactions on Instrumentation and Measurement 59 (4): 884–892.
   Web of Science ®Google Scholar
• Yang, B., and S. Li. 2012. “Pixel-Level Image Fusion with Simultaneous Orthogonal Matching Pursuit.” Information Fusion 13 (1): 10–19.
   Web of Science ®Google Scholar
• Yin, H., and S. Li. 2011. “Multimodal Image Fusion with Joint Sparsity Model.” Optical Engineering 50 (6): 067007–10.
   Web of Science ®Google Scholar
• Zhang, Q., and B.-L. Guo. 2007. “Fusion of Infrared and Visible Images Based on Non-Subsampled Contourlet Transform.” Journal of Infrared and Millimeter Waves 26 (6): 476–480.
   Web of Science ®Google Scholar
• Zhang, X., Q. Chen, and T. Men. 2009. “Comparison of Fusion Methods for the Infrared and Color Visible Images.” Paper presented at the 2009 2nd IEEE international conference on computer science and information technology, ICCSIT 2009, Beijing, August 8–11, 421–424.
   Google Scholar