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Physiological inverse tone mapping based on retina response

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Abstract

The mismatch between the Low Dynamic Range (LDR) content and the High Dynamic Range (HDR) display arouses the research on inverse tone mapping algorithms. In this paper, we present a physiological inverse tone mapping algorithm inspired by the property of the Human Visual System (HVS). It first imitates the retina response and deduce it to be local adaptive; then estimates local adaptation luminance at each point in the image; finally, the LDR image and local luminance are applied to the inversed local retina response to reconstruct the dynamic range of the original scene. The good performance and high-visual quality were validated by operating on 40 test images. Comparison results with several existing inverse tone mapping methods prove the conciseness and efficiency of the proposed algorithm.

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References

  1. Banterle, F., Debattista, K., Artusi, A., Pattanaik, S., Myszkowski, K., Ledda, P., Bloj, M., Chalmers, A.: High dynamic range imaging and low dynamic range expansion for generating HDR content. Comput. Graph. Forum 28(8), 2343–2367 (2009)

    Article  Google Scholar 

  2. Akyuz, O., Fleming, R., Riecke, B.E., Reinhard, E., Bulthoff, H.H.: Do HDR displays support LDR content? A psychophysical evaluation. ACM Trans. Graph. 26(3), 1–7 (2007)

    Article  Google Scholar 

  3. Masia, B., Agustin, S., Fleming, R.W., Sorkine, O., Gutierrez, D.: Evaluation of reverse tone mapping through varying exposure conditions. ACM Trans. Graph. 28(5), 1–8 (2009)

    Article  Google Scholar 

  4. Meylan, L., Daly, S., Susstrunk, S.: The reproduction of specular highlights on high dynamic range displays. In: Proceedings of the IST/SID 14th Color Imaging Conference, pp. 333–338. Society for Imaging Science and Technology (IS&T), Springfield (2006)

    Google Scholar 

  5. Didyk, P., Mantiuk, R., Hein, M., Seidel, H.P.: Enhancement of bright video features for hdr displays. Eurographics Symp. Render. 27(4), 1265–1274 (2008)

    Google Scholar 

  6. Masia, B., Fleming, R., Sorkine, O., Gutierrez, D.: Selective reverse tone mapping. In: Proceedings of CEIG (2010)

    Google Scholar 

  7. Wang, L., Wei, L.-Y., Zhou, K., Guo, B., Shum, H.-Y.: High dynamic range image hallucination. In: Eurographics Symposium on Rendering (2007)

    Google Scholar 

  8. Banterle, F., Ledda, P., Debattista, K., Chalmers, A.: Inverse tone mapping. In: Proc. 4th International Conf. Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, pp. 349–356. ACM, New York (2006)

    Google Scholar 

  9. Banterle, F., Ledda, P., Debattista, K., Chalmers, A., Bloj, M.: A framework for inverse tone mapping. Vis. Comput. (2007). doi:10.1007/s00371-007-0124-9

    Google Scholar 

  10. Banterle, F., Ledda, P., Debattista, K., Chalmers, A.: Expanding low dynamic range videos for high dynamic range applications. In: Proceedings of SCCG, pp. 349–356. ACM, New York (2008)

    Google Scholar 

  11. Rempel, A.G., Trentacoste, M., Seetzen, H., Young, H.D., Heidrich, W., Whitehead, L., Ward, G.: Ldr2hdr: on-the-fly reverse tone mapping of legacy video and photographs. ACM Trans. Graph. 26(3), 39 (2007)

    Article  Google Scholar 

  12. Kovaleski, R.P., Oliveira, M.M.: High quality brightness enhancement functions for real-time reverse tone mapping. Vis. Comput. (2009). doi:10.1007/s00371-009-0327-3

    Google Scholar 

  13. Keener, J., Sneyd, J.: Mathematical Physiology. Springer, New York (1998)

    MATH  Google Scholar 

  14. Dong, L., Su, J., Izquierdo, E.: Scene-oriented hierarchical classification of blurry and noisy images. IEEE Trans. Image Process. 21(5), 2534–2545 (2012)

    Article  MathSciNet  Google Scholar 

  15. Guarnieri, G., Marsi, S., Ramponi, G.: High dynamic range image display with halo and clipping prevention. IEEE Trans. Image Process. 20(5), 1351–1362 (2011)

    Article  MathSciNet  Google Scholar 

  16. Reinhard, E., Ward, G., Pattanaik, S., Debevec, P.: High Dynamic Range Imaging: Acquisition, Display and Image Based Lighting. Morgan Kaufmann, San Francisco (2005)

    Google Scholar 

  17. Boev, A., Poikela, M., Gotchev, A., Aksay, A.: Modelling of the Stereoscopic HVS (2012). http://www.google.fr/url?sa=t&rct=j&q=Modelling+of+the+Stereoscopic+HVS&source=web&cd=1&cad=rja&ved=0CCMQFjAA&url=http%3A%2F%2Fsp.cs.tut.fi%2Fmobile3dtv%2Fresults%2Ftech%2FD5.3_Mobile3DTV_v2.0.pdf&ei=PeOfUID5D5OzhAfZo4CgCA&usg=AFQjCNF5EgXz9c1HjtNWMwVZoAsoz6DgBA

  18. Daugman, J.G.: Two dimensional spectral analysis of cortical receptive field profiles. Vis. Res. 20(10), 847–856 (1980)

    Article  Google Scholar 

  19. Dowling, J.E.: The Retina: An Approachable Part of the Brain. Belknap Press, Cambridge (1987)

    Google Scholar 

  20. Shapley, R., Enroth-Cugell, C.: Visual adaptation and retinal gain-controls. Prog. Retin. Eye Res. 3, 263–346 (1984)

    Article  Google Scholar 

  21. Horiuchi, T., Tominaga, S.: HDR image quality enhancement based on spatially variant retinal response. EURASIP J. Image Video Process. (2010). doi:10.1155/2010/438958

    Google Scholar 

  22. Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high-dynamic-range images. In: Proceedings of SIGGRAPH, pp. 257–266. ACM, New York (2002)

    Google Scholar 

  23. Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM Trans. Graph. 21(3), 267–276 (2002)

    Article  Google Scholar 

  24. Aydin, T.O., Mantiuk, R., Myszkowski, K., Seidel, H.P.: Dynamic range independent image quality assessment. In: Proceedings SIGGRAPH, pp. 1–10. ACM, Los Angeles (2008)

    Google Scholar 

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Acknowledgements

This work was supported in part by the Postdoctoral Funds of the Burgundy Region of France, in part by the Fundamental Research Funds for the Central Universities (No. ZYGX2011J004), in part by the National Natural Science Foundation of China under Grant 61003123, and in part by the Fundamental Research Funds for the Central Universities (No. ZYGX2011X014).

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Authors and Affiliations

  1. LE2I-CNRS 6306 Laboratory, University of Burgundy, Dijon, 21078, France

    Yongqing Huo, Fan Yang & Vincent Brost

  2. School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Yongqing Huo

  3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Le Dong

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  1. Yongqing Huo
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  2. Fan Yang
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  3. Le Dong
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  4. Vincent Brost
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Correspondence to Yongqing Huo.

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Huo, Y., Yang, F., Dong, L. et al. Physiological inverse tone mapping based on retina response. Vis Comput 30, 507–517 (2014). https://doi.org/10.1007/s00371-013-0875-4

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