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Subjective evaluation of UHD video coded using VVC with LCEVC and ML-VVC

Naeem Ramzan, Muhammad Tufail Khan

TL;DR

This paper evaluates subjective quality of UHD video encoded with LCEVC as an enhancement layer on top of a VVC base using the MPEG multilayer test plan and LTM 8.1. The study compares LCEVC+VVC against upsampled VVC base and ML-VVC at two bitrate operating points $E10$ and $E50$ across 15 SDR/HDR sequences assessed by 25 participants with MOS and 95% CIs. Results show both LCEVC and ML-VVC deliver higher perceived quality than simple upsampling, with higher MOS at $E50$; direct comparison between LCEVC and ML-VVC yields no statistically robust difference under the tested conditions. The findings are specific to the tested configurations and do not address complexity or latency, but they inform decisions on multilayer coding options for UHD delivery. Overall, the work supports the viability of LCEVC as a competitive enhancement approach for VVC in terms perceptual quality.

Abstract

This paper presents the results of a subjective quality assessment of a multilayer video coding configuration in which Low Complexity Enhancement Video Coding (LCEVC) is applied as an enhancement layer on top of a Versatile Video Coding (VVC) base layer. The evaluation follows the same test methodology and conditions previously defined for MPEG multilayer video coding assessments, with the LCEVC enhancement layer encoded using version 8.1 of the LCEVC Test Model (LTM). The test compares reconstructed UHD output generated from an HD VVC base layer with LCEVC enhancement against two reference cases: upsampled VVC base layer decoding and multilayer VVC (ML-VVC). Two operating points are considered, corresponding to enhancement layers representing approximately 10% and 50% of the total bitrate. Subjective assessment was conducted using the Degradation Category Rating (DCR) methodology with twenty five participants, across a dataset comprising fifteen SDR and HDR sequences. The reported results include Mean Opinion Scores (MOS) with associated 95% confidence intervals, enabling comparison of perceptual quality across coding approaches and operating points within the defined test scope.

Subjective evaluation of UHD video coded using VVC with LCEVC and ML-VVC

TL;DR

This paper evaluates subjective quality of UHD video encoded with LCEVC as an enhancement layer on top of a VVC base using the MPEG multilayer test plan and LTM 8.1. The study compares LCEVC+VVC against upsampled VVC base and ML-VVC at two bitrate operating points and across 15 SDR/HDR sequences assessed by 25 participants with MOS and 95% CIs. Results show both LCEVC and ML-VVC deliver higher perceived quality than simple upsampling, with higher MOS at ; direct comparison between LCEVC and ML-VVC yields no statistically robust difference under the tested conditions. The findings are specific to the tested configurations and do not address complexity or latency, but they inform decisions on multilayer coding options for UHD delivery. Overall, the work supports the viability of LCEVC as a competitive enhancement approach for VVC in terms perceptual quality.

Abstract

This paper presents the results of a subjective quality assessment of a multilayer video coding configuration in which Low Complexity Enhancement Video Coding (LCEVC) is applied as an enhancement layer on top of a Versatile Video Coding (VVC) base layer. The evaluation follows the same test methodology and conditions previously defined for MPEG multilayer video coding assessments, with the LCEVC enhancement layer encoded using version 8.1 of the LCEVC Test Model (LTM). The test compares reconstructed UHD output generated from an HD VVC base layer with LCEVC enhancement against two reference cases: upsampled VVC base layer decoding and multilayer VVC (ML-VVC). Two operating points are considered, corresponding to enhancement layers representing approximately 10% and 50% of the total bitrate. Subjective assessment was conducted using the Degradation Category Rating (DCR) methodology with twenty five participants, across a dataset comprising fifteen SDR and HDR sequences. The reported results include Mean Opinion Scores (MOS) with associated 95% confidence intervals, enabling comparison of perceptual quality across coding approaches and operating points within the defined test scope.
Paper Structure (10 sections, 1 figure, 5 tables)

This paper contains 10 sections, 1 figure, 5 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. Dataset
  4. Brief decription of the test
  5. Configurations
  6. Quantization parameters
  7. Test design and execution
  8. Experimental Results
  9. Conclusion
  10. Acknowledgments

Figures (1)

  • Figure 1: Plots reporting, for each sequence, the MOS and CI for the three schemes: Base (grey), LCEVC E10 (dark green), ML-VVC E10 (light green), LCEVC E50 (dark purple) and ML-VVC E50 (light purple)