MDFI: A Multi-Domain Features Integration for Compressed Video Quality Enhancement
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Abstract (arXiv)
The latest video coding standard, H.266/VVC, has demonstrated significant improvements in compression efficiency compared to H.265/HEVC. Despite its advanced coding techniques, H.266/VVC still faces challenges in meeting the increasing demand for higher perceptual quality and enhanced compression performance. To address these limitations, we propose MDFI (Multi-Domain Features Integration), a compressed video quality enhancement approach that features a novel Frame-Prediction Feature Transform (FPFT) module to process prediction information. Moreover, MDFI integrates a multi-domain feature fusion strategy that effectively combines spatiotemporal characteristics, cross-frequency representations, and compressed-domain prediction information to enhance decoded video quality. Additionally, we introduce a comprehensive dataset that encompasses uncompressed video sequences, corresponding reconstructed versions at multiple QP levels, and predicted frames generated from H.266/VVC compressed bitstreams, providing essential resources for developing and benchmarking video enhancement approaches. Extensive experiments demonstrate that our MDFI approach achieves superior performance to state-of-the-art methods in both objective metrics and visual quality, effectively mitigating video compression artifacts. The code is available at: https://github.com/dangdinh17/MDFI.git.
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References · 16
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- 2015Compression Artifacts Reduction by a Deep Convolutional Networkcited by 136
- 2019MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Videocited by 50
- 2018Multi-Frame Quality Enhancement for Compressed Videocited by 48
- 2017Enhancing Quality for HEVC Compressed Videoscited by 28
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- 2024CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancementcited by 17
- 2021Recursive Fusion and Deformable Spatiotemporal Attention for Video Compression Artifact Reductioncited by 14
4 more
- 2022End-to-end Transformer for Compressed Video Quality Enhancementcited by 7
- 2024Compressed Video Quality Enhancement with Temporal Group Alignment and Fusioncited by 5
- 2025Enhancing Quality for VVC Compressed Videos with Omniscient Quality Enhancement Modelcited by 3
- 2025Compressed Video Quality Enhancement: Classifying and Benchmarking over Standardscited by 1
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