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Optimal exposure compression for high dynamic range content

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High dynamic range (HDR) imaging has become one of the foremost imaging methods capable of capturing and displaying the full range of lighting perceived by the human visual system in the real world. A number of HDR compression methods for both images and video have been developed to handle HDR data, but none of them has yet been adopted as the method of choice. In particular, the backwards-compatible methods that always maintain a stream/image that allow part of the content to be viewed on conventional displays make use of tone mapping operators which were developed to view HDR images on traditional displays. There are a large number of tone mappers, none of which is considered the best as the images produced could be deemed subjective. This work presents an alternative to tone mapping-based HDR content compression by identifying a single exposure that can reproduce the most information from the original HDR image. This single exposure can be adapted to fit within the bit depth of any traditional encoder. Any additional information that may be lost is stored as a residual. Results demonstrate quality is maintained as well, and better, than other traditional methods. Furthermore, the presented method is backwards-compatible, straightforward to implement, fast and does not require choosing tone mappers or settings.

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  1. 1.

    Banterle, F., Artusi, A., Debattista, K., Chalmers, A.: Advanced High Dynamic Range Imaging: Theory and Practice. A K Peters/CRC Press, Boca Raton (2011)

  2. 2.

    Akyüz, A.O., Reinhard, E.: Noise reduction in high dynamic range imaging. J. Vis. Commun. Image Represent. 18(5), 366–376 (2007)

  3. 3.

    Strgar Kurečić, M., Poljičak, A., Mandić, L.: A survey on the acceptance and the use of hdr photography among croatian photographers. Acta Gr. Znan. časopis Tisk. Graf. Komun. 24(1–2), 13–18 (2013)

  4. 4.

    Narwaria, M., Da Silva, M.P., Le Callet, P., Pepion, R. et al.: Impact of tone mapping in high dynamic range image compression. In: Proceedings of VPQM (2014)

  5. 5.

    Narwaria, M., Perreira Da Silva, M., Le Callet, P., Pepion, R.: Tone mapping based hdr compression: does it affect visual experience? Signal Process. Image Commun

  6. 6.

    Ward, G.: A contrast-based scalefactor for luminance display. In: Graphics Gems IV, pp. 415–421. Academic Press, New York (1994)

  7. 7.

    Ward, G.: LogLuv encoding for full-gamut. High-dynamic range images. J. Graph. Tools 3(1), 15–31 (1998)

  8. 8.

    Neumann, L., Matkovic, K., Purgathofer, W.: Automatic exposure in computer graphics based on the minimum information loss principle. In: Proceedings of the Computer Graphics International, pp. 666–677. IEEE, New York (1998)

  9. 9.

    Ward, G., Simmons, M.: Subband encoding of high dynamic range imagery. Proceedings of the 1st Symposium on Applied Perception in Graphics and Visualization—APGV ’04, p. 83. ACM Press, New York (2004)

  10. 10.

    Okuda, M., Adami, N.: Two-layer coding algorithm for high dynamic range images based on luminance compensation. J. Vis. Commun. Image Represent. 18(5), 377–386 (2007)

  11. 11.

    Xu, R., Pattanaik, S.N., Hughes, C.E.: High-dynamic-range still-image encoding in jpeg 2000. IEEE Comput. Graph. Appl. 25(6), 57–64 (2005)

  12. 12.

    Mantiuk, R., Myszkowski, K., Seidel, H.-P.: Lossy compression of high dynamic range images and video. In: Electronic Imaging 2006, pp. 60570V–60570V-10 (2006)

  13. 13.

    Lee, C., Kim, C.: Rate-distortion optimized compression of high dynamic range videos. In: Proceedings of the 16th European Signal Processing Conference (EUSIPCO 2008) (2008)

  14. 14.

    Eisemann, E., Durand, F.: Flash photography enhancement via intrinsic relighting. In: ACM Transactions on Graphics (TOG), vol. 23, pp. 673–678. ACM, New York (2004)

  15. 15.

    Mantiuk, R., Krawczyk, G., Myszkowski, K., Seidel, H.-P.: Perception-motivated high dynamic range video encoding. ACM Trans. Graph. 23(3), 733 (2004)

  16. 16.

    Motra, A., Thoma, H.: An adaptive Logluv transform for high dynamic range video compression. In: 2010 IEEE International Conference on Image Processing, pp. 2061–2064 (2010)

  17. 17.

    Zhang, Y., Reinhard, E., Bull, D.: Perception-based high dynamic range video compression with optimal bit-depth transformation. In: 8th IEEE International Conference on Image Processing, pp. 1321–1324 (2011)

  18. 18.

    Narwaria, M., Silva, M.P.D., Le Callet, P., Pepion, R.: Single exposure vs tone mapped high dynamic range images: a study based on quality of experience. In: 2013 Proceedings of the 22nd European Conference on Signal Processing (EUSIPCO), pp. 2140–2144. IEEE, New York (2014)

  19. 19.

    Narwaria, M., Da Silva, M.P., Le Callet, P., Pepion, R.: Effect of tone mapping operators on visual attention deployment. In: SPIE Optical Engineering \(+\) Applications, pp. 84990G–84990G. International Society for Optics and Photonics (2012)

  20. 20.

    Banterle, F., Artusi, A., Sikudova, E., Bashford-Rogers, T., Ledda, P., Bloj, M., Chalmers, A.: Dynamic range compression by differential zone mapping based on psychophysical experiments. In: Proceedings of the ACM Symposium on Applied Perception, pp. 39–46. ACM, New York (2012)

  21. 21.

    Freedman, D., Diaconis, P.: On the histogram as a density estimator: L2 theory. Probab. Theory Relat. Fields 57(4), 453–476 (1981)

  22. 22.

    Mantiuk, R., Efremov, A., Myszkowski, K.: Design and evaluation of backward compatible high dynamic range video compression. In: Technical Report (2006)

  23. 23.

    Lee, C., Kim, C.-S.: Gradient domain tone mapping of high dynamic range videos. In: 2007 IEEE International Conference on Image Processing, pp. III- 461–III-464. IEEE, New York (2007)

  24. 24.

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

  25. 25.

    Banterle, F., Ledda, P., Debattista, K., Chalmers, A.: Inverse tone mapping. In: Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia—GRAPHITE ’06, p. 349 (2006)

  26. 26.

    Banterle, F., Ledda, P., Debattista, K., Chalmers, A., Bloj, M.: A framework for inverse tone mapping. Vis. Comput. 23(7), 467–478 (2007)

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The Mercedes footage was provided by the University of Stuttgart, the Seine scene by Technicolor and Tears of Steel is an open movie project licensed under Creative Commons Attribution 3.0 by Blender (https://mango.blender.org/about/). Debattista is partially supported by a Royal Society Industrial Fellowship. Chalmers is partially supported by a Royal Society Industrial Fellowship.

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Correspondence to Kurt Debattista.

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Debattista, K., Bashford-Rogers, T., Selmanović, E. et al. Optimal exposure compression for high dynamic range content. Vis Comput 31, 1089–1099 (2015). https://doi.org/10.1007/s00371-015-1121-z

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  • High Dynamic Range
  • Single Exposure
  • Rate Distortion
  • Tone Mapper
  • High Dynamic Range Image