Extraction of well-exposed pixels for image fusion with a sub-banding technique for high dynamic range images

References

• Agarwala, A., et al., 2004. Interactive digital photomontage. ACM Transactions on Graphics, 23 (3), 294–302. doi:10.1145/1015706
   Web of Science ®Google Scholar
• Agrawal, A., et al., 2005. Removing photography artifacts using gradient projection and flash exposure sampling. ACM Transactions on Graphics, 24 (3), 828–835. doi:10.1145/1073204
   Web of Science ®Google Scholar
• Burt, P. and Adelson, E., 1983. The Laplacian pyramid as a Compact Image Code. IEEE Transactions on Communications, 31, 532–540. doi:10.1109/TCOM.1983.1095851
   Web of Science ®Google Scholar
• Burt, P.J. and Kolczynski, R.J., 1993. Enhanced image capture through fusion. In: Proceedings of the fourth international conference on computer vision, 11–14 May. IEEE.
   Google Scholar
• Crow, F.C., 1984. Summed–area tables for texture mapping. SIGGRAPH ’84: Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques, 18 (3), 207–212.
   Google Scholar
• Cvejic, N., et al., 2005. A similarity metric for assessment of image fusion algorithms. International Journal of Signal Processing, 2 (3), 178–182.
   Google Scholar
• Debevec, P.E. and Malik, J., 1997. Recovering high dynamic range radiance maps from photographs. In: Proceeding of SIGGRAPH 97, computer proceedings annual conference series, 369–378.
   Google Scholar
• Drago, F., et al., 2003. Adaptive logarithmic mapping for displaying high contrast scenes. Computer Graphics Forum, 22, 419–426. doi:10.1111/cgf.2003.22.issue-3
   Web of Science ®Google Scholar
• He, K., Sun, J., and Tang, X., 2013. Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35 (6), 1397–1409. doi:10.1109/TPAMI.2012.213
   PubMed Web of Science ®Google Scholar
• Hossny, M., Nahavandi, S., and Creighton, D., 2008. Comments on ‘information measure for performance of image fusion’. Electronics Letters, 44 (18), 1066–1067. doi:10.1049/el:20081754
   Web of Science ®Google Scholar
• Joffre, G., et al., 2005. High dynamic range images from digital cameras raw data. In: Proceedings of the ACM SIGGRAPH, 1 August 2005, 72.
   Google Scholar
• Kuang, J., Johnson, G.M., and Fairchild, M.D., 2007. iCAM06: a refined image appearance model for HDR image rendering. Journal of Visual Communication and Image Representation, 18 (5), 406–414. doi:10.1016/j.jvcir.2007.06.003
   Web of Science ®Google Scholar
• Li, S., Kang, X., and Hu, J., 2013. Image fusion with guided filtering. IEEE Transactions on Image Processing, 22 (7), 2864–2875. doi:10.1109/TIP.2013.2244222
   PubMed Web of Science ®Google Scholar
• Li, Z., Zheng, J., and Zhu, Z., 2015. Weighted image guided filtering. IEEE Transactions on Image Processing, 24 (1), 120–129.
   Web of Science ®Google Scholar
• Liu, Z., et al., 2012. Objective assessment of multi resolution image fusion algorithms for context enhancement in night vision: A comparative study. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34 (1), 94–109. doi:10.1109/TPAMI.2011.109
   PubMed Web of Science ®Google Scholar
• Qu, G., Zhang, D., and Yan, P., 2002. Information measure for performance of image fusion. Electronics Letters, 38 (7), 313–315. doi:10.1049/el:20020212
   Web of Science ®Google Scholar
• Raman, S., Kumar, V., and Chaudhuri, S., 2009. Blind de-ghosting for automatic multi-exposure compositing. In: Proceedings of SIGGRAPH ASIA 2009 posters. New York: ACM.
   Google Scholar
• Reinhard, E. and Devlin, K., 2005. Dynamic range reduction inspired by photoreceptor physiology. IEEE Transactions on Visualization and Computer Graphics, 11 (1), 13–24. doi:10.1109/TVCG.2005.9
   PubMed Web of Science ®Google Scholar
• Reinhard, E., et al., 2002. Photographic tone reproduction for digital images. In: Proceedings of the ACM SIGGRAPH, July 2002, 267–276.
   Google Scholar
• Rockinger, O., 1997. Image sequence fusion using a shift-invariant wavelet transform. In: Proceedings of the international conference on image processing, Washington, DC, USA, October 1997, vol. 3, 288–291.
   Google Scholar
• Shen, J., Zhao, Y., and He, Y., 2012. Detail preserving exposure fusion using subband architecture. The Visual Computer, 28, 463–473. doi:10.1007/s00371-011-0642-3
   Web of Science ®Google Scholar
• Shen, R., et al., 2011. Generalized random walks for fusion of multi-exposure images. IEEE Transactions on Image Processing, 20 (12), 3634–3646. doi:10.1109/TIP.2011.2150235
   PubMed Web of Science ®Google Scholar
• Tessens, L., et al., 2007. Extending the depth of field in microscopy through curvelet-based frequency-adaptive image fusion. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 1, 861–864.
   Google Scholar
• Tian, J. and Chen, L., 2012. Adaptive multi-focus image fusion using a wavelet based statistical sharpness measure. Signal Processing, 92 (9), 2137–2146. doi:10.1016/j.sigpro.2012.01.027
   Web of Science ®Google Scholar
• Tomasi, C. and Manduchi, R., 1998. Bilateral filtering for gray and color images. In: Computer vision, 1998. Sixth international conference on. IEEE, 839–84.
   Google Scholar
• Tsai, H.C., Lin, H.J., and Leou, J.J., 2015. Multiexposure image fusion using intensity enhancement and detail extraction. Journal of Visual Communication and Image Representation, 33, 165–178.
   Google Scholar
• Wang, Z., et al., 2004. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13 (4), 600–612. doi:10.1109/TIP.2003.819861
   PubMed Web of Science ®Google Scholar
• Xydeas, C. and Petrović, V., 2000. Objective image fusion performance measure. Electronics Letters, 36 (4), 308–309. doi:10.1049/el:20000267
   Web of Science ®Google Scholar
• Yang, C., et al., 2008. A novel similarity based quality metric for image fusion. Information Fusion, 9 (2), 156–160. doi:10.1016/j.inffus.2006.09.001
   Web of Science ®Google Scholar
• Zhang, Q. and Guo, B., 2009. Multifocus image fusion using the non subsampled contourlet transform. Signal Processing, 89 (7), 1334–1346. doi:10.1016/j.sigpro.2009.01.012
   Web of Science ®Google Scholar
• Zhao, J., Laganiere, R., and Liu, Z., 2007. Performance assessment of combinative pixel-level image fusion based on an absolute feature measurement. International Journal of Innovative Computing, Information and Control, 3 (6), 1433–1447.
   Google Scholar