Sep 2026· IEEE transactions on broadcasting· Vol 72, pp. 851-862· 0 citations· 45 references
Abstract
The exponential growth of global video traffic imposes severe constraints on available transmission bandwidth, necessitating continuous improvements in compression efficiency. While modern hybrid video codecs optimize bit allocation locally, they often fail to exploit the global characteristics, such as dominant edge directionality. To address this limitation, this paper proposes a bandwidth-efficient, lightweight pre-processing framework that adaptively mirrors encoded video frames to align their structural features with the encoder prediction tools. Unlike previous approaches that rely on computationally expensive brute-force search or complex neural networks, the proposed method uses a fast, heuristic decision algorithm based on edge-direction analysis. Extensive evaluations were conducted using the state of-the-art Enhanced Compression Model (ECM) and the industry-standard HEVC, covering both All-Intra and Random Access (RA) configurations to simulate realistic broadcasting scenarios. The results confirm that the framework yields noticeable coding gains, particularly for content with dominant diagonal geometric structures, achieving average BD-rate savings of <inline-formula> <tex-math notation="LaTeX">$\mathbf {-0.23\%}$ </tex-math></inline-formula> (ECM All-Intra) and <inline-formula> <tex-math notation="LaTeX">$\mathbf {-0.11\%}$ </tex-math></inline-formula> (ECM Random Access), with specific high-definition sequences (Class B) reaching gains up to <inline-formula> <tex-math notation="LaTeX">$\mathbf {-0.58\%}$ </tex-math></inline-formula>. Cross-codec validation using HEVC confirms the universality of the proposal, yielding an average savings of <inline-formula> <tex-math notation="LaTeX">$\mathbf {-0.30\%}$ </tex-math></inline-formula>. Crucially, complexity analysis reveals that the method introduces negligible computational overhead (approximately 30 ms of pre-analysis per 4K frame, making it a highly viable, lightweight extension for video distribution pipelines where reference encoder runtimes dominate.
The proposed S-NVRC spans a wide range of bitrate and decoding-complexity using a single encoding (training) and outperforms SHM 12.4 and the multi-layer VTM-20.0, by 43.7% and 5.6% in BD-rate on the UVG dataset, while also providing flexible complexity scalability.
Tian-Hao Peng, H. Kwan, Fan Zhang et al.· 0 citations
The suggested method presents an adaptive Image Compression (IC) and bandwidth matching method embedding a Rate-Distortion Auto-encoder enhanced Shrike Algorithm (RDAES) that provides a scalable, adaptive, and efficient solution for high-fidelity image transmission over constrained communication channels, ensuring low...
Zhongli Yi, Fu-Zhai Wang, Shan-Shan Wang et al.· Discover Internet of Things· 0 citations
This paper presents a CU-level dynamic approximate storage scheme for intra-frame prediction in Versatile Video Coding (VVC) encoders, targeting energy-efficient video compression. The proposed approach leverages the spatial-temporal correlation of intra-coded regions across neighboring Random Access (RA) frame layers...
Laiane Souza, Y. Camargo, Matheus Isquierdo et al.· Symposium on Integrated Circ...· 0 citations
The Versatile Video Coding (VVC) standard provides new tools that allow higher compression rates compared to previous standards, as well as greater adaptability to different types of video content, such as 360° or omnidirectional videos. In this sense, VVC requires a very high computational effort, especially in the in...
Rogerio Cassanta Rosado, Gustavo Sanchez, D. Palomino et al.· Journal of Integrated Circui...· 0 citations
A Video Compression framework built upon a foundational flow model that enables the compressor to harness generative video flow priors effectively, which reduces bit consumption by 58\% and achieves one-step decoding and reconstructions with high perceptual fidelity.
Yichong Xia, Qin-Hong Wu, Bin Chen et al.· 1 citation· ⚡1
This work proposes 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 to enhance decoded video quality.
Sang NguyenQuang, Hieu Bui Minh, BuiDinh Dang et al.· IEEE transactions on consume...· 0 citations
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