MMVD CPR Inter Prediction for Video Compression
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images and videos, such as UHD and immersive media, poses a challenge for efficient compression and transmission due to increased data volume, leading to higher transmission and storage costs.
Innovation Solution
The implementation of a method and apparatus that applies merge with motion vector difference (MMVD) in the process of current picture referencing (CPR) to improve video coding efficiency by configuring base motion information candidates, reducing computational complexity and enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image/video data are transmitted or stored using existing methods, then image quality and resolution are maintained, but transmission costs and storage costs increase significantly
Solution Approach 1:
The patent applies parameter changes by modifying motion vector precision from integer pixels to fractional pixels (e.g., 1/4-pixel or 1/8-pixel precision). This allows more accurate motion compensation without requiring higher resolution reference pictures, thereby maintaining image quality while reducing the need for high-bitrate transmission and storage
2Productivity
If conventional inter-prediction methods are used for CPR coding blocks, then coding simplicity is maintained, but coding efficiency and compression performance are insufficient
Solution Approach 1:
The patent introduces dynamic motion vector refinement by allowing fractional pixel precision adjustments based on the coding block type. For CPR coding blocks, fractional motion vectors are applied to improve prediction accuracy, while for non-CPR blocks, conventional integer precision is maintained, thus dynamically adapting complexity to need
Solution Approach 2:
The patent applies local quality by differentiating motion vector precision requirements between CPR coding blocks and non-CPR coding blocks. Fractional pixel precision is selectively applied only where needed (CPR blocks with temporal redundancy), rather than uniformly across all blocks, optimizing compression efficiency without unnecessary complexity
3Measurement precision
If fractional motion vector precision is applied to all coding blocks, then motion compensation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by differentiating motion vector precision requirements between CPR coding blocks and non-CPR coding blocks. Fractional pixel precision is selectively applied only where needed (CPR blocks with temporal redundancy), rather than uniformly across all blocks, optimizing compression efficiency without unnecessary complexity
Solution Approach 2:
The patent applies partial action by implementing fractional motion vector precision only for the specific case of CPR coding blocks where temporal redundancy exists, rather than applying it universally. This partial application achieves sufficient motion compensation accuracy for the problematic case without incurring the full computational cost across all blocks
Data Source
AI summary
An image decoding method performed by a decoding apparatus according to the present document comprises the steps of: determining that a merge with motion vector difference (MMVD) mode has been applied to a current block that is a current picture referencing (CPR) coding block referring to a current picture; deriving a base motion information candidate for the current block on the basis of candidate blocks neighboring the current block; generating prediction samples for the current block on the basis of the base motion information candidate; and generating reconstruction samples for the current block on the basis of the prediction samples, wherein the base motion information candidate is derived depending on whether the neighboring candidate blocks are CPR coding blocks.