Log In Sign Up

Predicting Chroma from Luma in AV1

Chroma from luma (CfL) prediction is a new and promising chroma-only intra predictor that models chroma pixels as a linear function of the coincident reconstructed luma pixels. In this paper, we present the CfL predictor adopted in Alliance Video 1 (AV1), a royalty-free video codec developed by the Alliance for Open Media (AOM). The proposed CfL distinguishes itself from prior art not only by reducing decoder complexity, but also by producing more accurate predictions. On average, CfL reduces the BD-rate, when measured with CIEDE2000, by 5


page 1

page 2

page 3

page 4


Predicting Chroma from Luma with Frequency Domain Intra Prediction

This paper describes a technique for performing intra prediction of the ...

Intra Prediction Using In-Loop Residual Coding for the post-HEVC Standard

A few years after standardization of the High Efficiency Video Coding (H...

Comparing Correspondences: Video Prediction with Correspondence-wise Losses

Today's image prediction methods struggle to change the locations of obj...

Progressive Spatial Recurrent Neural Network for Intra Prediction

Intra prediction is an important component of modern video codecs, which...

On Intra Prediction for Screen Content Video Coding

Screen content coding (SCC) is becoming increasingly important in variou...

The Hyper360 toolset for enriched 360^∘ video

360^∘ video is a novel media format, rapidly becoming adopted in media p...

uiCA: Accurate Throughput Prediction of Basic Blocks on Recent Intel Microarchitectures

Performance models that statically predict the steady-state throughput o...

Reference to Prior Literature


  • [1] Y. Wang, Y.-Q. Zhang, and J. Ostermann, Video Processing and Communications, 1st ed.   Upper Saddle River, NJ, USA: Prentice Hall PTR, 2001.
  • [2] L. Ze-Nian, M. S. Drew, and J. Liu, Fundamentals of Multimedia, 2nd ed.   Springer Publishing Company, Incorporated, 2014.
  • [3] J. Kim, S. Park, Y. Choi, Y. Jeon, and B. Jeon, “New intra chroma prediction using inter-channel correlation,” Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Tech. Rep. JCTVC-B021, Jul. 2010.
  • [4] J. Chen, V. Seregin, W.-J. Han, J. Kim, and B. Jeon, “Ce6.a.4: Chroma intra prediction by reconstructed luma samples,” Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Tech. Rep. JCTVC-E266, Mar. 2011.
  • [5] W. Pu, W.-S. Kim, J. Chen, K. Rapaka, L. Guo, J. Sole, and M. Karczewicz, “Non-rce1: Inter color component residual prediction,” Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Tech. Rep. JCTVC-N0266, Jul. 2013.
  • [6] S. Midtskogen, “Improved chroma prediction,” IETF NETVC Internet-Draft, Tech. Rep. draft-midtskogen-netvc-chromapred-02, Oct. 2016.
  • [7] N. E. Egge and J.-M. Valin, “Predicting chroma from luma with frequency domain intra prediction,” Proceedings of SPIE 9410, Visual Information Processing and Communication VI, vol. 9410, Mar. 2015.
  • [8] J.-M. Valin, T. B. Terriberry, N. E. Egge, T. Daede, Y. Cho, C. Montgomery, and M. Bebenita, “Daala: Building a next-generation video codec from unconventional technology,” Multimedia signal processing (MMSP) workshop, no. arXiv:1608.01947, Sep. 2016.
  • [9] T. Daede, A. Norkin, and I. Brailovsky, “Video codec testing and quality measurement,” IETF NETVC Internet-Draft, Tech. Rep. draft-ietf-netvc-testing-05, Mar. 2017.
  • [10] Xiph.Org Foundation, “Are We Compressed Yet?” [Online]. Available:
  • [11] M. Bebenita, “AV1 bitstream analyzer,” Mozilla. [Online]. Available:
  • [12] G. Bjøntegaard, “Calculation of average PSNR differences between RD-curves,” Video Coding Experts Group (VCEG) of ITU-T, Tech. Rep. VCEG-M33, 13th Meeting: Austin, Texas, USA, 2001.
  • [13] K. Egiazarian, J. Astola, N. Ponomarenko, V. Lukin, F. Battisti, and M. Carli, “Two new full-reference quality metrics based on HVS,” in Proceedings of the Second International Workshop on Video Processing and Quality Metrics for Consumer Electronics, VPQM, Jan. 2006.
  • [14] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE transactions on image processing, vol. 13, no. 4, pp. 600–612, Apr. 2004. [Online]. Available:
  • [15] Y. Yang, J. Ming, and N. Yu, “Color image quality assessment based on ciede2000,” advances in multimedia, vol. 2012, no. Article ID 273723, 2012,
  • [16] Z. Wang, E. P. Simoncelli, and A. C. Bovik, “Multiscale structural similarity for image quality assessment,” in The 37th Asilomar Conference on Signals, Systems Computers, vol. 2, Nov. 2003, pp. 1398–1402.
  • [17] T. Daede, “Test sets,” hosted by the Foundation. [Online]. Available:
  • [18] L. Trudeau, “Results of chroma from luma over the subset1 test set,” Are We Compressed Yet?, Nov. 2017. [Online]. Available:
  • [19] ——, “Results of chroma from luma over the objective-1-fast test set,” Are We Compressed Yet?, Nov. 2017. [Online]. Available:
  • [20] ——, “Results of chroma from luma over the twitch test set,” Are We Compressed Yet?, Nov. 2017. [Online]. Available: