Nothing Special   »   [go: up one dir, main page]

Skip to main content

High Dynamic Range Video Coding

  • Chapter
  • First Online:
Handbook of Signal Processing Systems

Abstract

Methods for the efficient coding of high-dynamic range (HDR) still-images and video sequences are reviewed. In dual-layer techniques, a base layer of standard-dynamic range data is enhanced by additional image data in an enhancement layer. The enhancement layer may be additive or multiplicative. If there is no requirement for backward compatibility, adaptive HDR-to-standard dynamic range (SDR) mapping schemes in the encoder allow for improved coding efficiency versus the backward-compatible schemes. In single-layer techniques, a base layer is complemented by metadata, such as supplementary enhancement information (SEI) data or color remapping information (CRI) data, which allow a decoder to apply special “reshaping” or inverse-mapping functions to the base layer to reconstruct an approximation of the original HDR signal. New standards for exchanging HDR signals, such as SMPTE 2084 and BT. 2100, define new mapping functions for translating linear scene light captured by a camera to video and are replacing the traditional “gamma” mapping. The effect of those transforms to existing coding standards, such as high efficiency video coding (HEVC) and beyond, are reviewed, and novel quantization and coding schemes that take these new mapping functions into consideration are also presented.

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

Access this chapter

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

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Candela per square meter (cd/m2), also referred to as nit, is the international standard unit of luminance.

  2. 2.

    “Tone mapping” refers to the process of mapping luminance values in a high dynamic range to luminance values in a lower dynamic range.

  3. 3.

    WCG stands for wide color gamut, referring to any color gamut larger than the color gamut supported by the original analog television systems and CRTs. For example, Rec. BT. 2020 [51] defines a WCG container for ultra-high-definition TVs.

  4. 4.

    BDVM stands for Blu-Ray Disc Movie.

References

  1. G. Ward and M. Simmons, "JPEG-HDR: A Backwards-Compatible, High Dynamic Range Extension to JPEG," ACM SIGGRAPH 2006.

    Google Scholar 

  2. A. Artusi et al. "JPEG XT: A compression standard for HDR and WCG images," IEEE Signal Processing Magazine, pp. 118-124, March 2016.

    Google Scholar 

  3. T. Richter, T. Bruylants, P. Schelkens, and T. Ebrahimi, “The JPEG XT Suite of standards: Status and Future Plans,” SPIE Optical Engineering+ Applications, International Society for Optics and Photonics, Sept. 2015.

    Google Scholar 

  4. Report ITU-R BT. 2390-0, "High dynamic range television for production and international programme exchange," ITU, 2016.

    Google Scholar 

  5. W. Gish and S. Miller, "Unambiguous video pipeline description motivated by HDR." In Proc. IEEE Intern. Conf. on Image Processing (ICIP 2016), pp. 909-912. IEEE, 2016.

    Google Scholar 

  6. P.G.J. Barten, “Contrast sensitivity of the human eye and its effects on image quality,” SPIE Optical Engineering Press: Bellingham, WA, 1999.

    Book  Google Scholar 

  7. S. Miller et al., "Perceptual Signal Coding for More Efficient Usage of Bit Codes," SMPTE Motion Imaging Journal, vol. 122:(4), pp. 52-59, May-June 2013.

    Google Scholar 

  8. Rec. ITU-R BT. 2100, "Image parameter values for high dynamic range television for use in production and international programme exchange," ITU, July 2016.

    Google Scholar 

  9. Rec. ITU-R BT. 1866, "Reference electro-optical transfer function for flat panel displays used in HDTV studio production," ITU, 03/2011.

    Google Scholar 

  10. R. Mantiuk, A. Efremov, K. Myszkowski, and H.-P. Seidel, "Backward Compatible High Dynamic Range MPEG Video Compression," ACM Trans. on Graphics 25(3):713-723, July 2006.

    Google Scholar 

  11. Z. Mai, H. Mansour, R. Mantiuk, P. Nasiopoulos, R. K. Ward and W. Heidrich, “Optimizing a Tone Curve for Backward-Compatible High Dynamic Range Image/Video Compression,” IEEE Trans. on Image Processing, Vol. 20, No. 6, pp. 1558 – 1571, June 2011.

    Google Scholar 

  12. G-M. Su, R. Atkins, and Q. Chen, "Backward-Compatible Coding for Ultra High Definition Video Signals with Enhanced Dynamic Range," US 9,549,207, January 17, 2017.

    Google Scholar 

  13. Q. Chen, G-M. Su, and P. Yin, “Near Constant-Time Optimal Piecewise LDR to HDR Inverse Tone Mapping,” IS&T/SPIE Electronic Imaging, 2015.

    Google Scholar 

  14. G-M. Su, S. Qu, H. Koepfer, Y. Yuan, and S. Hulyalkar, “Multiple Color Channel Multiple Regression Predictor," US 8,811,490 B2, 2014.

    Google Scholar 

  15. P. Bordes, P. Andrivon, X. Li, Y. Ye, and Y. He, "Overview of Color Gamut Scalability," IEEE Trans. on Circuits and Systems for Video Technology, March 2016.

    Google Scholar 

  16. G-M. Su, S. Qu, W. Gish, H. Koepfer, Y. Yuan, and S. Hulyalkar, “Image Prediction based on Primary Color Grading Model," US 8,731,287 B2, 2014.

    Google Scholar 

  17. "ASC Color Decision List (ASC CDL) Transfer Functions and Interchange Syntax," ASC Technology Committee Digital Intermediate Subcommittee, 2008

    Google Scholar 

  18. ITU Rec. H.265, “High efficiency video coding," Series H: Audiovisual and Multimedia Systems, Infrastructure of audiovisual services – Coding of Moving Video, ITU, Dec 2016.

    Google Scholar 

  19. S. Lasserre, E. François, F. Le Léannec, and D. Touzé, “Single-layer HDR video coding with SDR backward compatibility,” SPIE Optical Engineering+ Applications (pp. 997108-997108), September, 2016.

    Google Scholar 

  20. R. Goris, R. Brondijk, R. van der Vleuten, “Philips response to CfE for HDR and WCG,” m36266, ISO/IEC JTC1/SC29/WG11, Warsaw, Poland, July 2015.

    Google Scholar 

  21. G-M. Su, S. Qu, S. Hulyalkar, T. Chen, W. Gish, and H. Koepfer, “Layered Decomposition in Hierarchical VDR Coding," US 9,497,456 B2, November 15, 2016.

    Google Scholar 

  22. D. Flynn, D. Marpe, M. Naccari, T. Nguyen, C. Rosewarne, K. Sharman, J., and J. Xu "Overview of the range extensions for the HEVC standard: Tools, profiles, and performance," IEEE Trans. on Circuits and Systems for Video Technology, vol. 26, no. 1, pp 4-19, January, 2016.

    Google Scholar 

  23. F. Dufaux, P. Le Callet, R. Mantiuk, and M. Mrak, eds. “High Dynamic Range Video: From Acquisition, to Display and Applications, “Academic Press, 2016.

    Google Scholar 

  24. E. Francois, C. Gisquet, G. Laroche, P. Onno, “AHG18: On 16-bits Support for Range Extensions, Document,” JCTVC-N0142, 14th JCT-VC Meeting Vienna, Austria, Jul-Aug. 2013.

    Google Scholar 

  25. W. S. Kim, W. Pu, J. Chen, Y. K. Wang, J. Sole, M. Karczewicz, “AHG 5 and 18: High Bit-Depth Coding Using Auxiliary Picture, Document,” JCTVC-O0090, 15th JCT-VC Meeting, Geneva, Switzerland, Oct.-Nov. 2013.

    Google Scholar 

  26. A. Aminlou, K. Ugar, “On 16 Bit coding,” Document JCTVC-P0162, 16th JCT-VC Meeting, San Jose, CA, Jan. 2014.

    Google Scholar 

  27. C. Auyeung, J. Xu, “AHG 5 and 18, Coding of High Bit-Depth Source with Lower Bit-Depth Encoders and a Continuity Mapping,” Document JCTVC-P0173, 16th JCT-VC Meeting, San Jose, CA, Jan. 2014.

    Google Scholar 

  28. S. Lasserre, F. Le Leannec, P. Lopez, Y. Olivier, D. Touze, E. Francois, “High Dynamic Range Video Coding,” JCTVC-P0159 (m32076), 16th JCT-VC Meeting, San Jose, CA, Jan. 2014.

    Google Scholar 

  29. F. Le Leannec, S. Lasserre, E. Francois, D. Touze, P. Andrivon, P. Bordes, Y. Olivier, “Modulation Channel Information SEI Message,” Document JCTVC-R0139 (m33776), 18th JCT-VC Meeting, Sapporo, Japan, Jun.-Jul. 2014.

    Google Scholar 

  30. K. Sharman, N. Saunders, and J. Gamei, “AHG5 and 18:Internal Precision for High Bit Depths,” document JCTVC-N0188, 14th Meeting, JCT-VC, Vienna, Austria, Jul. 2013.

    Google Scholar 

  31. M. Karczewicz and R. Joshi, “AHG18: Limiting the Worst-Case Length for Coeff_Abs_Level_Remaining Syntax Element to 32 Bits,” document JCTVC-Q0131, 17th Meeting, JCT-VC, Valencia, Spain, Apr. 2014.

    Google Scholar 

  32. K. Sharman, N. Saunders, and J. Gamei, “AHG5 and AHG18: Entropy Coding Throughput for High Bit Depths,” document JCTVC-O0046, 15th Meeting, JCT-VC, Geneva, Switzerland, Oct. 2013.

    Google Scholar 

  33. A. Luthra, E. Francois, W. Husak, “Call for Evidence (CfE) for HDR and WCG Video Coding”, MPEG2014/N15083, 110th MPEG Meeting, Geneva, 2015.

    Google Scholar 

  34. K. Minoo, T. Lu, P. Yin, L. Kerofsky, D. Rusanovskyy, E. Francois, “Description of the Exploratory Test Model (ETM) for HDR/WCG extension of HEVC”, JCT-VC Doc. W0092, San Diego, CA, Feb. 2016.

    Google Scholar 

  35. L. Kerofsky, Y. Ye, and Y. He. "Recent developments from MPEG in HDR video compression," IEEE Intern. Conf. on Image Processing (ICIP), pp. 879-883. IEEE, 2016.

    Google Scholar 

  36. T. Lu, F. Pu, P. Yin, Y. He, L. Kerofsky, Y. Ye, Z. Gu, D. Baylon, “Compression Efficiency Improvement over HEVC Main 10 Profile for HDR and WCG Content,” Proc. of the IEEE Data Compression Conference (DCC), Snowbird, March 2016.

    Google Scholar 

  37. C. Wong, G-M. Su, M. Wu, “Joint Baseband Signal Quantization and Transform Coding for High Dynamic Range Video,” IEEE Signal Processing Letters, 2016.

    Google Scholar 

  38. T. Lu, F. Pu, P. Yin, J. Pytlarz, T. Chen, and W. Husak. "Adaptive reshaper for high dynamic range and wide color gamut video compression," SPIE Optical Engineering+ Applications, pp. 99710B-99710B, International Society for Optics and Photonics, 2016.

    Google Scholar 

  39. T. Lu, F. Pu, P. Yin, T. Chen, W. Husak, J. Pytlarz, R. Atkins, J. Fröhlich, G-M. Su, “ITP Colour Space and its Compression Performance for High Dynamic Range and Wide Colour Gamut Video Distribution,” ZTE Communications, Feb. 2016.

    Google Scholar 

  40. J. Ström, J. Samuelsson, and K. Dovstam, “Luma Adjustment for High Dynamic Range Video,” Proc. of the IEEE Data Compression Conference (DCC), Snowbird, March 2016.

    Google Scholar 

  41. T. Lu, P. Yin, T. Chen, and G-M. Su, "Rate Control Adaptation for High-Dynamic Range Images," U.S. Patent Application Publication US 2016/0134870, 2016.

    Google Scholar 

  42. J. Samuelsson et al., “Conversion and coding practices for HDR/WCG YCbCr 4:2:0 video with PQ transfer characteristics,” Draft new Supplement 15 to the H-Series of Recommendations, JCTVC-Z1017, 26-th meeting, Geneva, CH, Jan. 2017.

    Google Scholar 

  43. J. Ström, K. Andersson, M. Pettersson, P. Hermansson, J. Samuelsson, A. Segall, J. Zhao, S-H. Kim, K. Misra, A. M. Tourapis, Y. Su, and D. Singer, “High Quality HDR Video Compression using HEVC Main 10 Profile,” in Proc. of the IEEE Picture Coding Symposium (PCS), Nuremberg, 2016.

    Google Scholar 

  44. A. Norkin, “Fast algorithm for HDR video pre-processing,” in Proc. of the IEEE Picture Coding Symposium (PCS), Nuremberg, 2016.

    Google Scholar 

  45. R. Mantiuk, K. J. Kim, A. G. Rempel, and W. Heidrich. "HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions," ACM Trans. on Graphics (TOG), vol. 30, no. 4, p. 40. ACM, 2011.

    Google Scholar 

  46. M. Narwaria, M. P. Da Silva, and P. Le Callet. "HDR-VQM: An objective quality measure for high dynamic range video," Signal Processing: Image Communication, Vol. 35, pp. 46-60, 2015.

    Google Scholar 

  47. J. Froehlich, G-M. Su, S. Daly, A. Schilling, and B. Eberhardt. "Content aware quantization: Requantization of high dynamic range baseband signals based on visual masking by noise and texture," IEEE International Conf. on Image Processing (ICIP), pp. 884-888. IEEE, 2016.

    Google Scholar 

  48. S. Daly, "A visual model for optimizing the design of image processing algorithms," Proc. Intern. Conf. on Image Processing, (ICIP-94), vol. 2, pp. 16-20, 1994.

    Google Scholar 

  49. A. Lukin, "Improved visible differences predictor using a complex cortex transform," International Conf. on Computer Graphics and Vision, 2009.

    Google Scholar 

  50. Blu-Ray Disc Read-only Format, “Audio Visual Application Format Specifications for BD-ROM Version 3.1,” White Paper, August 2016, Blu-Ray Disc Association.

    Google Scholar 

  51. Rec. ITU-R BT. 2020-1, “Parameter values for ultra-high definition television systems for production and international programme exchange,” ITU, June 2014.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Konstantinos Konstantinides .

Editor information

Editors and Affiliations

Appendix: List of Abbreviations

Appendix: List of Abbreviations

AVC:

Advanced Video coding

BDVM HDR:

Blu-ray Disc Movie HDR

BL:

Base Layer

CAQ:

Content Adaptive Quantization

CfE:

Call for Evidence

CRI:

Color Remapping Information

CRT:

Cathode Ray Tube

EL:

Enhancement Layer

EOTF:

Electro-Optical Transfer Function

HDR:

High Dynamic Range

HDR ETM HDR:

Exploratory Test Model

HDTV:

High Definition Television

HEVC:

High Efficiency Video Coding

HLG:

Hybrid Log-Gamma

HVS:

Human Visual System

ITU:

International Telecommunication Union

JPEG:

Joint Photographic Experts Group

LDR:

Lower Dynamic Range

LSB:

Least Significant Bit

LUT:

Look-up Table

MMR:

Multivariate Multiple Regression

MPEG:

Moving Picture Experts Group

MSB:

Most Significant Bit

MSE:

Mean-Squared Error

NLQ:

Non-Linear Quantizer

OETF:

Opto-Electrical Transfer Function

OOTF:

Opto-Optical Transfer Function

PQ:

Perceptual Quantizer

PSNR:

Peak Signal-to-Noise Ratio

QP:

Quantization Parameter

RD:

Rate-Distortion

ROI:

Region of Interest

SDI:

Serial Digital Interface

SDR:

Standard Dynamic Range

SEI:

Supplementary Enhancement Information

SMPTE:

Society of Motion Picture and Television Engineers

TIFF:

Tagged Image File Format

UHD:

Ultra-high-definition

VDP:

Visual Difference Predictor

VQM:

Video Quality Measure

WCG:

Wide Color Gamut

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Konstantinides, K., Su, GM., Gadgil, N. (2019). High Dynamic Range Video Coding. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-91734-4_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-91734-4_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91733-7

  • Online ISBN: 978-3-319-91734-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics