Open Access

High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging

International Journal of Applied Mathematics and Computer Science's Cover Image
International Journal of Applied Mathematics and Computer Science
Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej

Cite

Aydin, T., Mantiuk, R., Myszkowski, K. and Seidel, H. (2008). Dynamic range independent image quality assessment, ACM Transactions on Graphics27(3): 1–10.10.1145/1360612.1360668Search in Google Scholar

Banterle, F., Artusi, A., Debattista, K. and Chalmers, A. (2011). Advanced High Dynamic Range Imaging: Theory and Practice, AK Peters (CRC Press), Natick, MA.10.1201/b11373Search in Google Scholar

Banterle, F., Artusi, A., Sikudova, E., Edward, T., Bashford-Rogers, W., Ledda, P., Bloj, M. and Chalmers, A. (2012). Dynamic range compression by differential zone mapping based on psychophysical experiments, ACM Symposium on Applied Perception, Los Angeles, CA, USA, pp. 39–46.Search in Google Scholar

Barten, P.G.J. (1999). Contrast Sensitivity of the Human Eye and Its Effects on Image Quality, SPIE, Washington, DC.10.1117/3.353254Search in Google Scholar

Bruce, N.D. (2014). Expoblend: Information preserving exposure blending based on normalized log-domain entropy, Computers & Graphics39: 12–23.10.1016/j.cag.2013.10.001Search in Google Scholar

Čadík, M., Wimmer, M., Neumann, L. and Artusi, A. (2008). Evaluation of HDR tone mapping methods using essential perceptual attributes, Computers & Graphics32(3): 330–349.10.1016/j.cag.2008.04.003Search in Google Scholar

Debevec, P. and Malik, J. (1997). Recovering high dynamic range radiance maps from photographs, ACM SIGGRAPH, pp. 369–378.Search in Google Scholar

Deng, G., Cahill, L.W. and Tobin, G.R. (1995). A study of logarithmic image processing model and its application to image enhancement, IEEE Transactions on Image Processing4(4): 506–512.10.1109/83.37068118290000Search in Google Scholar

Drago, F., Myszkowski, K., Annen, T. and Chiba, N. (2003). Adaptive logarithmic mapping for displaying high contrast scenes, Computer Graphics Forum22(3): 419–426.10.1111/1467-8659.00689Search in Google Scholar

Durand, F. and Dorsey, J. (2002). Fast bilateral filtering for the display of high-dynamic-range images, ACM Transactions on Graphics21(3): 257–266.10.1145/566654.566574Search in Google Scholar

Fattal, R., Lischinski, D. and Werman, M. (2002). Gradient domain high dynamic range compression, ACM Transactions on Graphics21(3): 249–256.10.1145/566654.566573Search in Google Scholar

Ferradans, S., Bertalmio, M., Provenzi, E. and Caselles, V. (2012). An analysis of visual adaptation and contrast perception for tone mapping, IEEE Transactions on Pattern Analysis and Machine Intelligence33(10): 2002–2012.10.1109/TPAMI.2011.4621383397Search in Google Scholar

Florea, C. and Florea, L. (2013). Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions, International Journal of Applied Mathematics and Computer Science23(3): 637–648, DOI: 10.2478/amcs-2013-0048.10.2478/amcs-2013-0048Search in Google Scholar

Gilchrist, A., Kossyfidis, C., Bonato, F., Agostini, T., Cataliotti, J., Li, X., Spehar, B., Annan, V. and Economou, E. (1999). An anchoring theory of lightness perception, Psychological Review106(4): 795–834.10.1037/0033-295X.106.4.795Search in Google Scholar

Grossberg, M.D. and Nayar, S.K. (2004). Modeling the space of camera response functions, IEEE Transactions on Pattern Analysis and Machine Intelligence26(10): 1272–1282.10.1109/TPAMI.2004.8815641715Search in Google Scholar

Jourlin, M. and Pinoli, J.C. (1987). Logarithmic image processing, Acta Stereologica6: 651–656.Search in Google Scholar

Krawczyk, G., Myszkowski, K. and Seidel, H.-P. (2005). Lightness perception in tone reproduction for high dynamic range images, Computer Graphics Forum24(3): 635–645.10.1111/j.1467-8659.2005.00888.xSearch in Google Scholar

Macmillan, N. and Creelman, C. (Eds.) (2005). Detection Theory: A User’s Guide, Lawrence Erlbaum, London.10.4324/9781410611147Search in Google Scholar

Mann, S. and Mann, R. (2001). Quantigraphic imaging: Estimating the camera response and exposures from differently exposed images, IEEE Computer Vision and Pattern Recognition, Kauai, HI, USA, Vol. 1, pp. 842–849.Search in Google Scholar

Mann, S. and Picard, R. (1995). Being ‘undigital’ with digital cameras: Extending dynamic range by combining differently exposed pictures, Proceedings of IS&Ts 48th Annual Conference, San Jose, CA, USA, Vol. 1, pp. 422–428.Search in Google Scholar

Marković, D. and Jukić, D. (2013). On parameter estimation in the bass model by nonlinear least squares fitting the adoption curve, International Journal of Applied Mathematics and Computer Science23(1): 145–155, DOI: 10.2478/amcs-2013-0012.10.2478/amcs-2013-0012Search in Google Scholar

Mertens, T., Kautz, J. and Reeth, F.V. (2007). Exposure fusion, Proceedings of Pacific Graphics, Maui, HI, USA, pp. 382–390.Search in Google Scholar

Meylan, L., Alleysson, D. and Susstrunk, S. (2007). Model of retinal local adaptation for the tone mapping of color filter array images, Journal of Optical Society of America A24(9): 2807–2816.10.1364/JOSAA.24.00280717767249Search in Google Scholar

Naka, K.-I. and Rushton, W.A.H. (1966). S-potentials from luminosity units in the retina of fish (cyprinidae), The Journal of Physiology185(3): 587–599.10.1113/jphysiol.1966.sp00800313958325918060Search in Google Scholar

Navarro, L., Courbebaisse, G. and Deng, G. (2013). The symmetric logarithmic image processing model, Digital Signal Processing23(5): 1337–1343.10.1016/j.dsp.2013.07.001Search in Google Scholar

Panetta, K., Zhou, Y., Agaian, S. and Wharton, E. (2011). Parameterized logarithmic framework for image enhancement, IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics41(2): 460–472.10.1109/TSMCB.2010.205884720977986Search in Google Scholar

Patrascu, V. and Buzuloiu, V. (2001). Color image enhancement in the framework of logarithmic models, 8th IEEE International Conference on Telecommunications, Bucharest, Romania, Vol. 1, pp. 199–204.Search in Google Scholar

Pece, F. and Kautz, J. (2010). Bitmap movement detection: HDR for dynamic scenes, Proceedings of the Conference on Visual Media Production, London, UK, pp. 1–8.Search in Google Scholar

Pinoli, J.C. and Debayle, J. (2007). Logarithmic adaptive neighborhood image processing (LANIP): Introduction, connections to human brightness perception, and application issues, EURASIP Journal on Advances in Signal Processing1: 114–114, Paper no. 036105.Search in Google Scholar

Reinhard, E., Stark, M., Shirley, P. and Ferwerda, J. (2002). Photographic tone reproduction for digital images, ACM Transactions on Graphics21(3): 267–276.10.1145/566654.566575Search in Google Scholar

Reinhard, E., Ward, G., Pattanaik, S. and Debevec, P. (2005). High Dynamic Range Imaging: Acquisition, Display and Image-Based Lighting, Morgan Kaufmann Publishers, San Francisco, CA.10.1016/B978-012585263-0/50010-5Search in Google Scholar

Robertson, M., Borman, S. and Stevenson, R. (1999). Dynamic range improvement through multiple exposures, International Conference on Image Processing, Kobe, Japan, pp. 159–163.Search in Google Scholar

Stevens, J. and Stevens, S. (1963). Brightness functions: Effects of adaptation, Journal of Optical Society of America A53(3): 375–385.10.1364/JOSA.53.000375Search in Google Scholar

Stevens, S. (1961). To honor Fechner and repeal his law, Science133(3446): 80–133.10.1126/science.133.3446.80Search in Google Scholar

Tamburino, D., Alleysson, D., Meylan, L. and Strusstruk, S. (2008). Digital camera workflow for high dynamic range images using a model of retinal process, in D. Tamburrino, et al. (Eds.), IS&T/SPIE Electronic Imaging: Digital Photography IV, San Jose, CA, USA.Search in Google Scholar

Valeton, J. and van Norren, D. (1983). Light adaptation of primate cones: An analysis based on extracellular data, Vision Research23(12): 1539–1547.10.1016/0042-6989(83)90167-0Search in Google Scholar

Vertan, C., Oprea, A., Florea, C. and Florea, L. (2008). A pseudo-logarithmic framework for edge detection, Advanced Concepts for Intelligent Vision Systems, Juan-les-Pins, France, pp. 637–644.Search in Google Scholar

Wang, Z., Bovik, A.C., Sheikh, H.R. and Simoncelli, E.P. (2004). Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing13(4): 600–612.10.1109/TIP.2003.819861Search in Google Scholar

Ward, G., Rushmeier, H. and Piatko, C. (1997). A visibility matching tone reproduction operator for high dynamic range scenes, IEEE Transactions on Visualization and Computer Graphics3(4): 291–306.10.1109/2945.646233Search in Google Scholar

Yeganeh, H. and Wang, Z. (2013). Objective quality assessment of tone mapped images, IEEE Transactions on Image Processing22(2): 657–667.10.1109/TIP.2012.222172523047872Search in Google Scholar

Zhang, W. and Cham, W.-K. (2012). Gradient-directed multi-exposure composition, IEEE Transactios on Image Processing21(4): 2318–2323.10.1109/TIP.2011.217007921965210Search in Google Scholar

eISSN:
2083-8492
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Mathematics, Applied Mathematics