A Transformer-Based Intra Luma Enhancement for H.266/VVC

Intra prediction is essential in reducing spatial domain correlation in video coding. To improve intra prediction accuracy, we introduce a transformer-based quality enhancement method aiming atimproving the luma quality of reconstructed coding tree units (CTUs). Our transformer-based model, namely Enhanceformer, utilizes multi-head attention for comprehensive feature extraction across multiple stages, levels, and scales. By integrating the model into H.266/VVC codec, it not only improves the luma quality of the current reconstructed CTU, but also provides more accurate references for intra prediction of subsequent CTUs. Experimental results show that this method achieves average BD rate savings of 2.63%, 0.21% and 0.48% for Y, Cb and Cr components respectively in all intra configuration, outperforming H.266/Versatile Video Coding (VVC) anchor.