Frame-level quality and memory traffic allocation for lossy embedded compression in video codec systems
Li Guo, Dajiang Zhou, Shinji Kimura, Satoshi Goto

TL;DR
This paper introduces a novel frame-level approach for allocating quality and memory traffic in lossy embedded video compression, significantly improving PSNR and consistency over traditional methods.
Contribution
It is the first to optimize video quality and memory traffic at the frame level, addressing error propagation and outperforming non-reference-only allocation strategies.
Findings
Outperforms non-reference-only allocation by up to 4.5 dB PSNR.
Achieves more consistent quality with lower PSNR fluctuation.
Provides an efficient frame-level allocation method for hierarchical-B GOPs.
Abstract
For mobile video codecs, the huge energy dissipation for external memory traffic is a critical challenge under the battery power constraint. Lossy embedded compression (EC), as a solution to this challenge, is considered in this paper. While previous studies in EC mostly focused on compression algorithms at the block level, this work, to the best of our knowledge, is the first one that addresses the allocation of video quality and memory traffic at the frame level. For lossy EC, a main difficulty of its application lies in the error propagation from quality degradation of reference frames. Instinctively, it is preferred to perform more lossy EC in non-reference frames to minimize the quality loss. The analysis and experiments in this paper, however, will show lossy EC should actually be distributed to more frames. Correspondingly, for hierarchical-B GOPs, we developed an efficient…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Coding and Compression Technologies · Advanced Data Compression Techniques · Image and Video Quality Assessment
