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.

Motion Estimation (ME) is one of the most computationally intensive module in H.266/VVC, and Fractional Motion Estimation (FME) accounts for the majority of its complexity. While substantial research efforts have been devoted to affine motion estimation (AME) and integer motion estimation (IME), studies on FME optimization remain limited. In this paper, a fast FME algorithm is proposed based on motion vector (MV) correlation from spatially adjacent coding units (CUs). The overall pipeline of the algorithm is illustrated in Fig. 1. The algorithm utilizes FME results from neighboring CUs to guide the FME process for the current CU. A buffer is maintained to store motion information from recently encoded CUs. During FME processing, the current CU retrieves information about adjacent CUs from this buffer. For half-pixel search, the algorithm first identifies integer motion vector (IMV)-similar CUs from the buffer, defined as CUs whose MVs differ from the current CU's IMV by no more than 0.75 pixels in both horizontal and vertical dimensions. For each IMV-similar CU, the motion vector offset (MVO), calculated as the difference between the cached CU's MV and the current CU's IMV, is computed and mapped to one of nine half-pixel search directions. The occurrences of each direction are accumulated, and if the count for any direction satisfies a statistically derived threshold, the half-pixel search is restricted to that specific direction. When the fast half-pixel search condition is satisfied, quarter-pixel search is performed utilizing the selected IMV-similar CUs. For each of these CUs, the quarter-pixel motion vector offset (QMVO) is calculated as the difference between the cached CU's MV and the predicted half-pixel MV obtained from the fast half-pixel search. Each QMVO is mapped to a specific quarter-pixel search pattern, and if the occurrence count for any pattern meets a statistically derived threshold, the quarter-pixel search is restricted to that pattern. Experimental results under the VVenC 1.12.0 medium preset show that the proposed algorithm achieves an average encoding time saving of 1.44% with only a 0.20% BD-rate increase.

The Moving Picture Experts Group (MPEG) is developing a new generation of the mesh coding standard, called Video-based Dynamic Mesh Coding (V-DMC). This standard represents a dense original mesh using a sparser base mesh, combined with a subdivision scheme and a set of displacement vectors that indicate the disparities between the subdivided base mesh and the deformed mesh, which approximates the original mesh. However, the lossy compression of the base mesh introduces displacement biases. Moreover, the one-dimensional encoding of these vectors, while saving bits, also leads to a loss of displacement information. In this paper, we propose a modified encoding framework to enhance the representation of displacement, thereby correcting biases and reducing information loss. Our method involves post-deformation to ensure the deformed mesh aligns with the reconstructed base mesh. Furthermore, by optimizing the deformed mesh corresponding to the reconstructed base mesh, more information is preserved in the encoded displacements, thus improving the quality of the reconstructed mesh. Experimental results show significant BD-rate gains over the V-DMC test model version 8.0, leading to its adoption in the V-DMC test model version 9.0.