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SSIM-Variation-Based Complexity Optimization for Versatile Video Coding
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DOI：10.1109/LSP.2022.3227748.png)
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摘要
En 中文
Hitherto, Versatile Video Coding (VVC) has a more magnificent overall performance than High Efficiency Video Coding (HEVC). The Quadtree with Nested Multi-Type Tree (QTMT) coding block structure can substantially enhance video coding quality in VVC. However, the coding gain also leads to a greater coding complexity. Therefore, this letter proposes a Fast Decision Scheme Based on Structural Similarity Index Metric Variation (FDS-SSIMV) to solve this problem. Firstly, the Structural Similarity Index Metric Variation (SSIMV) characteristic among the sub coding units of the spit mode is illustrated. Next, to evaluate the SSIMV value, SSIMV measure strategies are designed for different split modes in this letter. Then, the desired split modes are selected by the SSIMV values. Experimental results show that the proposed method achieves an average encoding Time Saving (TS) and Bjontegaard Delta Bit Rate (BDBR) with 64.74% and 2.79%, respectively, outperforming the benchmarks.
Keyword:
Versatile video voding
inter prediction
supervised contrastive learning
complexity optimization