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

2026-01-15

AI Summary

This study systematically evaluates the impact of LCEVC enhancement layers superimposed on a VVC base layer on the subjective quality of UHD video. Within a unified test framework, a Degradation Category Rating (DCR) subjective experiment compares the perceptual quality of HD VVC+LCEVC reconstructed UFD video against two reference approaches—upsampled VVC and ML-VVC—at enhancement layer bitrates of 10% and 50%. Based on Mean Opinion Scores (MOS) with 95% confidence intervals derived from 15 SDR/HDR sequences, this work provides the first quantitative assessment of the subjective quality differences among the three coding configurations across varying bitrates, offering empirical evidence for the practical gains of LCEVC in multilayer video coding.

Technology Category

• Computer Vision: Video Understanding & Activity Analysis
• Machine Learning: Large Multimodal Models (LMMs)
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

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.

Problem

• subjective quality assessment
• UHD video
• VVC
• LCEVC
• multilayer video coding

Innovation

• LCEVC
• VVC
• subjective quality assessment
• multilayer video coding
• UHD