通过自适应块向量替换，提升视频编码中非相邻区域的预测效率。
Enhanced Template-based Intra Mode Derivation with Adaptive Block Vector Replacement
- 用块向量预测扩展模板法的参考范围至非邻近区域。
- 在全帧内模式下比ECM-16.1降低0.082%码率，屏幕内容再降0.25%。
- 保持原有复杂度，适合需要高效率视频压缩的研究与工程应用。
帧内预测是传统视频编码框架中的关键组件，旨在消除帧内空间冗余。近年来，越来越多的解码器端自适应模式推导方法被引入增强压缩模型（ECM）。然而，这些方法主要依赖相邻空间信息进行帧内模式决策，忽略了非相邻空间区域的潜在相似性模式，从而限制了帧内预测效率。为此，本文提出一种基于模板的帧内模式推导方法，通过块向量预测进行增强。自适应块向量替换策略有效将现有模板法的参考范围扩展至非相邻空间信息，从而提升预测效率。大量实验表明，该策略在全帧内（AI）配置下，相较于ECM-16.1，Y分量实现0.082%的Bjøntegaard delta rate（BD-rate）节省，且编码/解码复杂度保持不变；在屏幕内容序列上进一步实现0.25%的额外BD-rate节省。
原文摘要 · Abstract (English)
Intra prediction is a crucial component in traditional video coding frameworks, aiming to eliminate spatial redundancy within frames. In recent years, an increasing number of decoder-side adaptive mode derivation methods have been adopted into Enhanced Compression Model (ECM). However, these methods predominantly rely on adjacent spatial information for intra mode decision-making, overlooking potential similarity patterns in non-adjacent spatial regions, thereby limiting intra prediction efficiency. To address this limitation, this paper proposes a template-based intra mode derivation approach enhanced by block vector-based prediction. The adaptive block vector replacement strategy effectively expands the reference scope of the existing template-based intra mode derivation mode to non-adjacent spatial information, thereby enhancing prediction efficiency. Extensive experiments demonstrate that our strategy achieves 0.082% Bjøntegaard delta rate (BD-rate) savings for Y components under the All Intra (AI) configuration compared to ECM-16.1 while maintaining identical encoding/decoding complexity, and delivers an additional 0.25% BD-rate savings for Y components on screen content sequences.
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