A Cross-Component Prediction Model For Screen Content Coding

Current video coding schemes such as VVC and ECM employ separate palette coding for luma and chroma components under dual-tree structure, ignoring cross-component correlations. Although there are linear and multi-modal linear models to capture cross-component correlations, such models are not tailored for screen content sequences. To address this, we propose a novel cross-component prediction model for screen content sequences. The proposed method builds on the core observation that, regions of screen content sequences comprise of few distinct colors and luma value (almost always) uniquely conveys chroma values. In the light of this observation, the proposed method derives chroma prediction based on a discrete mapping function between luma and chroma values. Specifically, the method simply remembers the reconstructed luma values and their corresponding chroma values in a look-up table and employs this look-up table for cross-component prediction for the current chroma block. To achieve higher accuracy, a multi-filter approach is employed to derive co-located luma values. For an example configuration, the proposed method achieves 1.37%, 1.08% and 1.68% Y, U and V bit-rate savings respectively over ECM 3.1, for text and graphics media under all-intra configuration, demonstrating its efficacy.