Adaptive Up-Sampling Filter for RPR-Based Video Reconstruction
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in intra prediction and motion vector prediction, leading to suboptimal compression ratios and increased bandwidth requirements due to the use of less likely prediction directions and redundant data representation.
Innovation Solution
Implementing an adaptive up-sampling filter that applies different filter coefficient sets based on the directionality and activity of local gradients for luma and chroma samples, using reference picture resampling to optimize reconstruction quality without secondary adaptive loop filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional intra prediction is used, then the decoding process is simple, but compression efficiency is low and bandwidth requirements increase
Solution Approach 1:
The patent segments the current block into multiple subblocks (e.g., four quadrants) and applies different filter coefficient sets to each subblock based on its gradient characteristics. This segmentation allows tailored filtering that improves compression efficiency while managing complexity through localized processing
Solution Approach 2:
The patent applies local quality by determining gradient directionality and activity for each subblock and selecting appropriate filter coefficient sets accordingly. Different regions receive different filtering treatments based on their specific characteristics, optimizing compression for each local area while avoiding unnecessary processing elsewhere
2Manufacturing precision
If more filter coefficient sets are applied for better reconstruction, then quality improves, but processing time increases
Solution Approach 1:
The patent applies partial action by selecting and applying only the necessary filter coefficient sets based on gradient analysis. Rather than exhaustively testing all possible filters, the system determines the optimal subset for each subblock, achieving good reconstruction quality while minimizing processing time through informed selection
Solution Approach 2:
The patent changes parameters by adapting filter coefficient sets based on gradient directionality and activity characteristics of different subblocks. This parameter adaptation allows the system to optimize reconstruction quality for each region while controlling processing time through efficient parameter selection rather than exhaustive search
Data Source
AI summary
Coded information indicates that an adaptive up-sampling filter is applied to a current block in a current picture. A respective class for each of a plurality of subblocks of the current block is determined. A respective filter coefficient set is determined for each of the plurality of subblocks from a plurality of filter coefficient sets of the adaptive up-sampling filter. The respective filter coefficient set is determined based on at least one class corresponding to the respective subblock and a respective sampling rate of reference pixel resampling (RPR) applied on a reference picture of the current picture. The respective sampling rate is associated with one of a plurality of phases of the RPR. The adaptive up-sampling filter is applied to the current block to generate filtered reconstructed samples of the current block based on the determined respective filter coefficient sets without applying a secondary adaptive loop filter (ALF).