2021/08/26 by Jingning Han, Paul Wilkins, Han, Jingning +6
Computer Science · Engineering · #Advanced Data Compression Techniques #Advanced Vision and Imaging #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Video Coding and Compression Technologies #eess.IV #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2108.11586
arxiv created 2021/08/26 · openalex publication_date 2021/08/26 · arxiv updated 2021/08/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Motion compensated prediction is central to the efficiency of video compression. Its predictive coding scheme propagates the quantization distortion through the prediction chain and creates a temporal dependency. Prior research typically models the distortion propagation based on the similarity between original pixels under the assumption of high resolution quantization. Its efficacy in the low to medium bit-rate range, where the quantization step size is largely comparable to the magnitude of the residual signals, is questionable. This work proposes a quantitative approach to estimating the temporal dependency. It evaluates the rate and distortion for each coding block using the original and the reconstructed motion compensation reference blocks, respectively. Their difference effectively measures how the quantization error in the reference block impacts the coding efficiency of the current block. A recursive update process is formulated to track such dependency through a group of pictures. The proposed scheme quantifies the temporal dependency more accurately across a wide range of operating bit-rates, which translates into considerable coding performance gains over the existing contenders as demonstrated in the experiments.