The Non-Separable Transform (NST) is an effective transform algorithm for improving coding efficiency in H.266/Versatile Video Coding (VVC) and Beyond VVC. In this paper, we propose an adaptive reordering strategy and fast pruning techniques on the encoder side to optimize the transform kernel selection of NST. The absolute sum values of forward transform coefficients (CoefAbsSum) are used as a coefficients energy criterion for evaluating transform kernels: a smaller CoefAbsSum indicates a better transformation of the kernel. Two key technical efforts are designed: we first propose an adaptive reordering for NST transform kernels, which sorts the three transform kernels in each prediction mode's transform set according to CoefAbsSum. It thereby prioritizes kernels with better potential Rate-Distortion (RD) performance. Subsequently, we design three fast algorithms for the sorted kernels, including adjusted RD cost threshold pruning, CoefAbsSum-based pre-screening, and historical RD performance comparison to skip modes with poor preestimates. Experimental results, conducted based on ECM 17.0, show that the proposed framework achieves an average encoding time reduction of 1.3 % (with the encoding time ratio of 98.7 %); meanwhile, it maintains a BD-rate change of 0.00 % for the Y component, 0.03 % for the Cb component, and 0.01 % for the Cr component. The Beyond VVC is an exploration platform with extremely high coding complexity, and our work reduces the complexity while introducing nearly no coding loss.

Adaptive loop filter (ALF), including luma ALF, chroma ALF, and cross-component adaptive loop filter (CCALF), has been adopted in H.266/versatile video coding (VVC). It can enhance the quality of reconstructed videos based on the Wiener filtering principle. In-depth analyses reveal that the efficiency of chroma ALF and CCALF is significantly lower than that of luma ALF, primarily due to the insufficient number of chroma-related filter sets in the adaptation parameter sets (APSs). To address this limitation, this paper focuses on the efficient design of ALF APSs. Specifically, we propose a luma-guided rate-distortion optimization (RDO) criterion for chroma components to improve the efficiency of the new ALF APS. Furthermore, an improved ALF APS list management is introduced to extend the lifetime of chroma-related filter sets in the ALF APS list.

Cloud gaming is a popular paradigm in the gaming industry, allowing real-time gaming experiences powered by cloud computing. Due to a strict latency sensitivity, efficient video encoding is crucial for its wide application. Cloud gaming videos are produced by game engines, which provide auxiliary data such as rendered generative motion vectors (RG-MVs). These motion vectors, calculated by 3D geometry and representing ground-truth motion, offer significant potential for fast video coding design.