Inter-channel correlation is one of the redundancy which need to be eliminated in video coding. In the latest video coding standard H.266/VVC, the DM (Direct Mode) and CCLM (Cross-component Linear Model) modes have been introduced to reduce the similarity between luminance and chroma. However, inter-channel correlation is still observed. In this paper, a new inter-channel prediction algorithm is proposed, which utilizes coloring principle to predict chroma pixels. From the coloring perspective, for most natural content video frames, the three components Y, U and V always demonstrate similar coloring pattern. Therefore, the U and V components can be predicted using the coloring pattern of the Y component. In the proposed algorithm, correlation coefficients are obtained in a lightweight way to describe the coloring relationship between current pixel and reference pixel in Y component, and used to predict chroma pixels. The optimal position for the reference samples is also designed. Base on the selected position of the reference samples, two new chroma prediction modes are defined. Experiment results show that, compared with VTM 12.1, the proposed algorithm has an average of -0.92% and -0.96% BD-rate improvement for U and V components, for All Intra (AI) configurations. At the same time, the increased encoding time and decoding time can be ignored.

In previous machine learning based fast intra mode decision algorithms for screen content videos, feature design is a key task and it is always difficult to obtain distinguishable features. In this paper, the idea of interaction of features is introduced to fast video coding algorithm, and a fast intra mode decision algorithm based on feature cross is proposed for screen content videos. The numeric features and category features are designed based on the characteristics of screen content videos, and the adaptive factorization network (AFN) is improved and adopted to carry out feature interaction to designed features, and output distinguishable features. The experimental results show that for AI (All Intra) configuration, compared with standard VVC/H.266, the coding time is reduced by 29.64% and the BD rate is increased only by 1.65%.