Adaptive Upscaling Filter Selection with Wiener Filter Compression Techniques in Reference Picture Resampling

Encoding video frames at adaptive resolutions has been shown to be an effective strategy, as it balances the trade-off between side information and residual data based on frame size and content. Reference Picture Resampling (RPR) in the Versatile Video Coding (H.266/VVC) standard allows for motion compensation between frames with different resolutions, overcoming the limitation that resolution switching points must occur at intra random-access points (IRAP), and that all frames within a closed GOP must be encoded at a single resolution. Frame rescaling is a critical step in RPR; however, applying a single upscaling filter to all video frames of different resolutions is not ideal. In this paper, an adaptive upscaling filter selection scheme is proposed, which incorporates Wiener filter trained at the frame level. The rate-distortion (RD) performance of various upscaling filters is compared to determine the optimal adaptive filter. The Wiener filter coefficients are reduced and compressed using predictive coding. Experimental results on VVC test model (VTM) 23.3 show average BD rate gains of 0.33% for 4K, 2.15% for 1080p and 2.11% for 480p video sequences at a 2.0x RPR scaling ratio under random-access configurations. At a 1.5x RPR scaling ratio, the BD rate gains are 0.57% for 4K, 2.22% for 1080p and 4.71% for 480p video sequences.