Subsampled Sum-Modified-Laplacian for Adaptive Loop Filter in Versatile Video Coding

Abstract

This paper proposes a Subsampled Sum-Modified-Laplacian (SSML) operator for the block classification of the Adaptive Loop Filter (ALF) in Versatile Video Coding (VVC). The VVC Test Model (VTM)-2.0 includes Geometry transformation-based ALF (GALF) with $4\times 4$ block classification, a single $7\times 7$ Luma diamond-shaped filter, and spatial adaptation at the Coding Tree Block (CTB) level to improve the coding efficiency of VVC. However, in the $4\times 4$ block classification, 1-D (1-Dimensional) Modified-Laplacian (ML) values for various directions are calculated at all sample positions within an $8\times 8$ window, and these are summed to derive the gradients for the corresponding directions. For a CTB where the Wiener filter is applied, every $4\times 4$ Luma block within the CTB must calculate Sum-Modified-Laplacian (SML) operations, which results in increased computational complexity of the decoder. Therefore, four different subsampling patterns based on $4\times 4$ block classification for the SSML operator that calculate the 1-D ML values at subsampled sample positions within the $8\times 8$ window are proposed as attempts to reduce the computational complexity of the block classification process in the ALF of VTM-2.0. As all of the proposed subsampling patterns reduce the number of sample positions needed to calculate the 1-D ML operations by half, the experimental results demonstrate that the proposed method achieves total decoding time reductions in the range of 2% to 3%, while the coding gain of the ALF is maintained.