Skip to main content
Log in

Revertible tone mapping of high dynamic range imagery: Integration to JPEG 2000

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper presents a revertible tone mapping approach based on subband architecture where the dynamic range of the HDR (High Dynamic Range) image is decreased to LDR (Low Dynamic Range) to fit several types of applications. The LDR image can be later expanded to get back the original HDR content. One important benefit of the proposed approach is its backward compatibility with low dynamic (LDR) image applications since no extra information is needed to perform a very efficient HDR reconstruction. In order to improve the efficiency of our TM (Tone Mapping), we couple it with an optimisation procedure to minimize the reconstruction error. Subjective and objective comparisons with state-of-the-art methods have shown superior quality results of both tone mapped and reconstructed images. As a potential application, the integration of the proposed tone mapping to JPEG 2000 encoder achieved competitive performance compared to reference HDR image encoders.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. http://www.mathworks.com/matlabcentral/linkexchange/links/2792-the-hdr-toolbox

  2. http://sourceforge.net/projects/hdrvdp/files/hdrvdp/

References

  1. Akyüz AO, Fleming R, Riecke BE, Reinhard E, Bülthoff HH (2007) Do hdr displays support ldr content?: A psychophysical evaluation. ACM Trans Graph 26

  2. Bamberger R, Smith M (1992) A filter bank for the directional decomposition of images: Theory and design. IEEE Trans Signal Process 40:882–893

    Article  Google Scholar 

  3. Banterle F, Artusi A, Sikudova E, Bashford-Rogers T, Ledda P, Bloj M, Chalmers A (2012) Dynamic range compression by differential zone mapping based on psychophysical experiments Proceedings of the ACM Symposium on Applied Perception, SAP ’12. ACM, NY, USA, pp 39–46

    Chapter  Google Scholar 

  4. Banterle F, Ledda P, Debattista K, Chalmers A (2006) Inverse tone mapping Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, GRAPHITE ’06. ACM, NY, USA, pp 349–356

    Chapter  Google Scholar 

  5. Bruce N (2014) ExpoBlend: Information preserving exposure blending based on norMalized log-domain entropy. Comput Graph 39:12–23

    Article  Google Scholar 

  6. Cohen J, Tchou C, Hawkins T, Debevec P (2001) Real-time high dynamic range texture mapping Proceedings of the 12th Eurographics Workshop on Rendering Techniques. Springer-Verlag, UK, pp 313–320

    Google Scholar 

  7. Durand F, Dorsey J (2002) Fast bilateral filtering for the display of high-dynamic-range images. ACM Trans Graph (TOG) 21:257–266

    Google Scholar 

  8. Drago F, Myszkowski K, Annen T, Chiba N (2003) Adaptive logarithmic mapping for displaying high contrast scenes. Comput Graph Forum 22:419–426

    Article  Google Scholar 

  9. Fattal R, Lischinski D, Werman M (2002) Gradient domain high dynamic range compression Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’02. ACM, NY, USA, pp 249–256

    Chapter  Google Scholar 

  10. Jianping Z, Minh N (2005) Multidimensional oversampled lter banks. In: Wavelet Applications Signal Image Processing XI

  11. Jobson D, Rahman Z-u, Woodell G (1997) A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans Image Process 6:965–976

    Article  Google Scholar 

  12. Landis H (2002) Production-ready global illumination. In: Siggraph Course Notes 16

  13. Li Y, Sharan L, Adelson E (2005) Compressing and companding high dynamic range images with subband architectures. ACM Trans Graph (TOG) 24:836–844

    Article  Google Scholar 

  14. Liu L, Liu B, Huang H, Bovik AC (2014) No-reference image quality assessment based on spatial and spectral entropies. Signal Process Image Commun 29 (8):856–863

    Article  Google Scholar 

  15. Ma K, Yeganeh H, Zeng K, Wang Z (2015) High dynamic range image compression by optimizing tone mapped image quality index. IEEE Trans Image Process 24:3086–3097

    Article  MathSciNet  Google Scholar 

  16. Mantiuk R, Kim K, Rempel A, Heidrich W (2011) Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions. ACM Trans Graph (TOG) 30:40,1–40,14

    Article  Google Scholar 

  17. Meylan L, Daly S, Sǎijsstrunk S (2006) The reproduction of specular highlights on high dynamic range displays, In: In IST/SID 14th Color Imaging Conference

  18. Mittal A, Soundararajan R, Bovik A (2013) Making a ”completely blind” image quality analyzer. Signal Process Lett, IEEE 20:209–212

    Article  Google Scholar 

  19. Munkberg J, Clarberg P, Hasselgren J, Akenine-Möller T. (2006) High dynamic range texture compression for graphics hardware. ACM Trans Graph (TOG) 25:698–706

    Article  MATH  Google Scholar 

  20. Pattanaik S, Ferwerda J, Fairchild M, Greenberg D (1998) A multiscale model of adaptation and spatial vision for realistic image display Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’98. ACM, NY, USA, pp 287–298

    Chapter  Google Scholar 

  21. Pattanaik S, Tumblin J, Yee H, Greenberg D (2000) Time-dependent visual adaptation for fast realistic image display Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’00. ACM Press/Addison-Wesley Publishing Co., NY, USA, pp 47–54

    Chapter  Google Scholar 

  22. Pece F, Kautz J (2010) Bitmap movement detection: Hdr for dynamic scenes Proceedings of the 2010 Conference on Visual Media Production, CVMP ’10. IEEE Computer Society, DC, USA , pp 1–8

    Google Scholar 

  23. Richter PST, Bruylants T, Ebrahimi T (2015) The jpeg xt suite of standards: status and future plans. In: Proceedings of SPIE: Applications of Digital Image Processing XXXVIII, 9599

  24. Reinhard E, Devlin K (2005) Dynamic range reduction inspired by photoreceptor physiology. IEEE Trans Vis Comput Graph 11:13–24

    Article  Google Scholar 

  25. Scheel A, Stamminger M, Seidel H (2000) Tone reproduction for interactive walkthroughs. Comput Graph Forum 19(3):301–311

    Article  Google Scholar 

  26. Smith M, Eddins S (1990) Analysis/synthesis techniques for subband image coding. IEEE Trans Acoust, Speech Signal Process 38:1446–1456

    Article  Google Scholar 

  27. Taubman D, Marcellin M (2000) JPEG 2000: Image compression fundamentals, Standards and practice. Kluwer Academic Publishers, MA, USA, p 2001

    Google Scholar 

  28. Tumblin J, Hodgins J, Guenter B (1999) Two methods for display of high contrast images. ACM Trans Graph 18(1):56–94

    Article  Google Scholar 

  29. Tumblin J, Turk G (1999) LCIS: A Boundary hierarchy for detail-preserving contrast reduction Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’99. ACM Press/Addison-Wesley Publishing Co., NY, USA, pp 83–90

    Chapter  Google Scholar 

  30. Vetterli M, Kovačevic J (1995) Wavelets and subband coding. Prentice-Hall, Inc., NJ, USA

    MATH  Google Scholar 

  31. Ward G (1994) Graphics gems iv, ch. A Contrast-based Scalefactor for Luminance Display. Academic Press Professional, Inc., CA, USA, pp 415–421

    Google Scholar 

  32. Ward G, Simmons M (2006) JPEG-HDR: A Backwards-compatible, High Dynamic Range Extension to JPEG ACM SIGGRAPH 2006 Courses, SIGGRAPH ’06. ACM, NY, USA

    Google Scholar 

  33. Xiang Z, Milanfar P (2010) Automatic parameter selection for denoising algorithms using a no-reference measure of image content. IEEE Trans Image Process 19:3116–3132

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  Google Scholar 

  35. Yeganeh H, Zhou W (2013) Objective quality assessment of tone-mapped images. IEEE Trans Image Process 22:657–667

    Article  MathSciNet  MATH  Google Scholar 

  36. Zhang Y, Naccari M, Agrafiotis D, Mrak M, Bull DR (2016) High dynamic range video compression exploiting luminance masking. IEEE Trans Circ Syst Vid Technol 26:950–964

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Ouled Zaid.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bouzidi, I., Ouled Zaid, A. & Larabi, M.C. Revertible tone mapping of high dynamic range imagery: Integration to JPEG 2000. Multimed Tools Appl 77, 5215–5239 (2018). https://doi.org/10.1007/s11042-017-4425-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-4425-3

Keywords