DMVR Inter Prediction Using Block Size and Bi-Prediction Weighting
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images and videos, along with the rise of immersive media formats, necessitates a high-efficiency image and video compression technology to reduce transmission and storage costs while maintaining quality.
Innovation Solution
Implementing a decoder-side motion vector refinement (DMVR) and bi-directional optical flow (BDOF) for inter prediction, with conditions to determine their application based on block size and bi-prediction weight index, enhancing coding efficiency and reducing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image and video data 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 block size parameters. Different refinement techniques (DMVR, BDOF) are selected according to the size of the current block, optimizing the balance between compression efficiency and computational complexity for different resolution levels
Solution Approach 2:
The patent segments the image processing into different blocks and applies appropriate refinement techniques to each block based on its size. This allows high-quality compression for large blocks while using simpler methods for small blocks, reducing overall computational cost
2Productivity
If motion vector refinement is applied to improve prediction accuracy, then coding efficiency is improved, but calculation complexity increases
Solution Approach 1:
The patent changes the refinement parameters based on block size and bi-prediction weight index. The system selects different refinement methods (full DMVR, partial DMVR, or no refinement) according to the block dimensions and prediction mode, optimizing the trade-off between coding efficiency and computational complexity
Solution Approach 2:
The patent applies partial refinement action by selectively applying DMVR and BDOF only to blocks that require it based on size thresholds. Not all blocks receive full refinement treatment, reducing overall computational load while maintaining coding efficiency for critical regions
Data Source
AI summary
An image decoding method performed by a decoding device according to the present document comprises the steps of: deriving a motion vector for a current block; determining whether to apply refinement to the motion vector for the current block; deriving a refined motion vector by applying decoder-side motion vector refinement (DMVR) to the motion vector if it is determined to apply refinement to the motion vector for the current block; deriving prediction samples for the current block on the basis of the refined motion vector; and generating reconstruction samples for the current block on the basis of the prediction samples, wherein the step of determining whether to apply refinement includes determining whether to apply the refinement on the basis of at least one of the size of the current block and bi-prediction weight index information for the current block.