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 × 4 block classification, a single 7 × 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 × 4 block classification, 1-D (1-Dimensional) ModifiedLaplacian (ML) values for various directions are calculated at all sample positions within an 8 × 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 × 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 × 4 block classification for the SSML operator that calculate the 1-D ML values at subsampled sample positions within the 8 × 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.

Keywords

• Adaptive loop filter (ALF)
• block classification
• in-loop filter
• versatile video coding (VVC)
• video coding