Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
157 tokens/sec
GPT-4o
43 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Video Compression Beyond VVC: Quantitative Analysis of Intra Coding Tools in Enhanced Compression Model (ECM) (2404.07872v1)

Published 11 Apr 2024 in cs.MM and eess.IV

Abstract: A quantitative analysis of post-VVC luma and chroma intra tools is presented, focusing on their statistical behaviors, in terms of block selection rate under different conditions. The aim is to provide insights to the standardization community, offering a clearer understanding of interactions between tools and assisting in the design of an optimal combination of these novel tools when the JVET enters the standardization phase. Specifically, this paper examines the selection rate of intra tools as function of 1) the version of the ECM, 2) video resolution, and 3) video bitrate. Additionally, tests have been conducted on sequences beyond the JVET CTC database. The statistics show several trends and interactions, with various strength, between coding tools of both luma and chroma.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (26)
  1. B. Bross et al., “Overview of the versatile video coding (VVC) standard and its applications,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 10, pp. 3736–3764, 2021.
  2. W. Hamidouche et al., “Versatile video coding standard: A review from coding tools to consumers deployment,” IEEE Consumer Electronics Magazine, vol. 11, no. 5, pp. 10–24, 2022.
  3. X. Li et al, “JVET-AG0007: AHG report ECM tool assessment (AHG7),” in 33rd JVET meeting: January, 2024.
  4. M. Coban et al, “JVET-AG2025: Algorithm description of Enhanced Compression Model 12 (ECM 12),” in 33rd JVET meeting: January, 2024.
  5. Y. Liu et al., “Statistical analysis of inter coding in VVC test model (VTM),” in 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022, pp. 3456–3459.
  6. M. Abdoli et al., “JVET-AH0227: AHG7: Statistical analysis of luma and chroma intra tools in ECM versions,” in 34th JVET meeting: April, 2024.
  7. F. Galpin et al, “JVET-AG2019: Description of algorithms and software in neural network-based video coding (NNVC) version 6,” in 33rd JVET meeting: January, 2024.
  8. K. Cao et al., “JVET-W0123: Fusion for template-based intra mode derivation,” in 23rd JVET meeting: July, 2021.
  9. M. Abdoli et al., “JVET-O0449: Decoder-side Intra Mode Derivation (DIMD) with prediction fusion using Planar,” in 15th JVET meeting: July, 2020.
  10. F. Wang et al., “JVET-0155: Combination of spatial GPM tests,” in 28th JVET meeting: October, 2022.
  11. L. Xu et al., “JVET-AB0157: Combination of EE2-1.10 and EE2-1.11,” in 28th JVET meeting: October, 2022.
  12. J. Pfaff et al., “Data-driven intra-prediction modes in the development of the versatile video coding standard,” ITU J. ICT Discoveries, vol. 3, no. 1, pp. 25–32, 2020.
  13. K. Naser et al., “JVET-AB0130: IntraTMP adaptation for camera-captured content,” in 28th JVET meeting: October, 2022.
  14. L. Wang et al., “JVET-AD0086: Combination of IntraTMP tests,” in 30th JVET meeting: April, 2023.
  15. R. G. Youvalari et al, “Filtered intra template matching prediction for future video coding,” in 2023 31st European Signal Processing Conference (EUSIPCO). IEEE, 2023, pp. 576–579.
  16. C. C. Chen et al., “JVET-AD0208: IBC adaptation for coding of natural content,” in 30th JVET meeting: April, 2023.
  17. J. Pfaff et al., “Intra prediction and mode coding in VVC,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 10, pp. 3834–3847, 2021.
  18. J. Lainema et al., “JVET-Z0050: Combined intra prediction tests,” in 26th JVET meeting: April, 2022.
  19. M. Abdoli et al., “Gradient-based intraprediction fusion for video coding,” IEEE MultiMedia, vol. 28, no. 3, pp. 88–96, 2020.
  20. R. G. Youvalari et al., “Joint cross-component linear model for chroma intra prediction,” in 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2020, pp. 1–5.
  21. P. Astola et al., “JVET-AA0057: Convolutional cross-component intra prediction model,” in 27th JVET meeting: July, 2022.
  22. P. Astola et al., “JVET-AA0126: Combined tests of EE2-1.1a, 1.1b and 1.2,” in 27th JVET meeting: July, 2022.
  23. K. Zhang et al., “JVET-AD0188: Non-local cross-component prediction and cross-component merge mode,” in 30th JVET meeting: April, 2023.
  24. J.-Y Huo et al., “JVET-AC0070: Direct block vector mode for chroma prediction,” in 29th JVET meeting: January, 2023.
  25. M. Karczewicz et al., “JVET-AE2017: Common test conditions and evaluation procedures for enhanced compression tool testing,” in 31st JVET meeting: July, 2023.
  26. D. Ma et al., “BVI-DVC: A training database for deep video compression,” IEEE Transactions on Multimedia, vol. 24, pp. 3847–3858, 2021.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now