HMD-TMO: A Tone Mapping Operator for 360\(^\circ \) HDR Images Visualization for Head Mounted Displays

  • Ific GoudéEmail author
  • Rémi Cozot
  • Francesco Banterle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11542)


We propose a Tone Mapping Operator, denoted HMD-TMO, dedicated to the visualization of 360\(^\circ \) High Dynamic Range images on Head Mounted Displays. The few existing studies about this topic have shown that the existing Tone Mapping Operators for classic 2D images are not adapted to 360\(^\circ \) High Dynamic Range images. Consequently, several dedicated operators have been proposed. Instead of operating on the entire 360\(^\circ \) image, they only consider the part of the image currently viewed by the user. Tone mapping a part of the 360\(^\circ \) image is less challenging as it does not preserve the global luminance dynamic of the scene. To cope with this problem, we propose a novel tone mapping operator which takes advantage of both a view-dependant tone mapping that enhances the contrast, and a Tone Mapping Operator applied to the entire 360\(^\circ \) image that preserves global coherency. Furthermore, we present a subjective study to model lightness perception in a Head Mounted Display.


Head Mounted Display High Dynamic Range Tone Mapping Operator 360\(^\circ \) image 



All 360\(^\circ \) HDR images come from free SYNS and LizardQ datasets. This work has been supported by the ANR project ANR-17-CE23-0020. We would like to thank Kadi Bouatouch for his help and proofreading. Thanks to all experiment participants for their contributions.


  1. 1.
    Perrin, A.-F., Bist, C., Cozot, R., Ebrahimi, T.: Measuring quality of omnidirectional high dynamic range content. In: Optics+Photonics Optical Engineering+Applications Applications of Digital Image Processing XL, p. 38 (2017)Google Scholar
  2. 2.
    Melo, M., Bouatouch, K., Bessa, M., Coelho, H., Cozot, R., Chalmers, A.: Tone mapping HDR panoramas for viewing in head mounted displays. In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, pp. 232–239 (2018)Google Scholar
  3. 3.
    Yu, M.: Dynamic tone mapping with head-mounted displays. Standford University Report. 5 (2015)Google Scholar
  4. 4.
    Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. In: Conference on Computer Graphics and Interactive Techniques, vol. 29, pp. 267–276 (2002)Google Scholar
  5. 5.
    Cutchin, S., Li, Y.: View Dependent Tone Mapping of HDR Panoramas for Head Mounted Displays. The Eurographics Association (2016)Google Scholar
  6. 6.
    Fechner, G.T., Howes, D.H., Boring, E.G.: Elements of psychophysics, vol. 1. Holt, Rinehart and Winston, New York (1966)Google Scholar
  7. 7.
    Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K.: High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting, vol. 238, 2nd edn. Elsevier, Amsterdam (2010)Google Scholar
  8. 8.
    Fairchild, M.D.: Color Appearance Models. Wiley, Hoboken (2013)CrossRefGoogle Scholar
  9. 9.
    Larson, G.W., Rushmeier, H., Piatko, C.: A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Trans. Vis. Comput. Graph. 3(4), 291–306 (1997)CrossRefGoogle Scholar
  10. 10.
    Schlick, C.: Quantization techniques for visualization of high dynamic range pictures. In: Sakas, G., Müller, S., Shirley, P. (eds.) Photorealistic Rendering Techniques. Focus on Computer Graphics (Tutorials and Perspectives in Computer Graphics), pp. 7–20. Springer, Heidelberg (1995). Scholar
  11. 11.
    Yeganeh, H., Wang, Z.: Objective quality assessment of tone mapped images. IEEE Trans. Image Process. 22(2), 657–667 (2013)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Univ Rennes, CNRS, IRISARennesFrance
  2. 2.Visual Computing LabISTI-CNRPisaItaly

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