Conditional DMVR Inter-Prediction Using Minimum SAD
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images and videos, particularly in immersive media formats like VR and AR, necessitates a high-efficiency image and video compression technology to reduce transmission and storage costs while maintaining image quality.
Innovation Solution
The implementation of decoder-side motion vector refinement (DMVR) and bi-directional optical flow (BDOF) in inter prediction processes to enhance coding efficiency by refining motion vectors and determining application conditions for these techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality images and videos are transmitted, then image quality is improved, but transmission costs and storage costs increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting motion vector refinement based on application conditions. The DMVR process modifies motion vector parameters (L0 and L1 motion vectors) through iterative optimization, changing the precision and characteristics of motion compensation parameters to achieve better compression efficiency at high resolutions without proportionally increasing transmission costs
Solution Approach 2:
The patent implements dynamics by making the motion vector refinement process adaptive and conditional. The system dynamically determines whether to apply DMVR based on specific application conditions (such as picture type, block size, and motion characteristics), allowing the system to adjust its complexity and computational resources based on the actual content and transmission requirements
2Productivity
If decoder-side motion vector refinement is applied to enhance prediction accuracy, then coding efficiency is improved, but calculation complexity increases
Solution Approach 1:
The patent applies partial action by implementing DMVR only when specific application conditions are met, rather than universally applying the full refinement process. The system evaluates conditions such as picture type (I, P, or B pictures), block size thresholds, and motion vector characteristics to determine when partial refinement is sufficient and when full DMVR is necessary, optimizing the balance between coding efficiency and computational complexity
Solution Approach 2:
The patent implements local quality by applying different levels of motion vector refinement to different blocks and regions. The system evaluates local characteristics such as block size, motion vector magnitude, and prediction mode to determine the appropriate refinement level for each specific region, rather than applying uniform processing across the entire image or video sequence
3Manufacturing precision
If bi-directional optical flow is applied to improve prediction performance, then coding accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies periodic action through iterative optimization processes in the DMVR algorithm. The motion vector refinement occurs in multiple iterations where prediction accuracy is progressively improved through periodic updates of motion vectors and corresponding prediction samples, allowing the system to achieve high accuracy through systematic, staged processing rather than single-pass computation
Data Source
AI summary
An image decoding method comprises the steps of: determining whether or not an application condition of decoder-side motion vector refinement (DMVR) for applying motion vector refinement for a current block is satisfied; deriving a minimum sum of absolute differences (SAD) on the basis of L0 and L1 motion vectors of the current block if the application condition of the DMVR is satisfied; deriving refined L0 and L1 motion vectors of the current block based on the minimum SAD; deriving prediction samples of the current block based on the refined L0 and L1 motion vectors; and generating reconstructed samples of the current block based on the prediction samples. With respect to whether or not the application condition of the DMVR is satisfied, the application condition of the DMVR is determined to be satisfied if a prediction mode, in which inter-prediction and intra-prediction are combined, is not applied to the current block.