Affine Motion Prediction Using Subblock Temporal Merge Candidates
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to increased transmission and storage costs due to the higher amount of information required, necessitating a more efficient image compression technique.
Innovation Solution
An affine motion prediction-based image decoding method that constructs an affine merge candidate list using subblock-based temporal merging candidates derived from motion vectors of neighboring blocks, reducing operational complexity and improving coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional image compression techniques are used for high-resolution images, then transmission and storage costs increase due to the larger amount of information, but using more efficient compression techniques can reduce these costs while maintaining image quality
Solution Approach 1:
The current block is divided into sub-blocks, and motion prediction is performed separately for each sub-block. This segmentation allows for more precise local motion compensation while reducing the overall computational complexity by processing smaller regions independently, thereby improving compression efficiency without sacrificing image quality.
Solution Approach 2:
The patent employs affine motion models that can dynamically adapt to different types of motion (translation, rotation, scaling, shearing) by adjusting motion parameters based on the characteristics of each sub-block. This dynamic approach allows the compression technique to maintain high image quality across various motion scenarios while optimizing transmission efficiency.
2Productivity
If affine motion prediction with subblock-based temporal merge candidates is used, then coding efficiency improves, but computational complexity increases due to the additional candidate derivation and list construction processes
Solution Approach 1:
Temporal merge candidates are derived in advance from previously decoded pictures and stored in a candidate list. This preliminary action allows the decoder to quickly access pre-computed motion information without performing complex calculations during the current picture decoding, thereby improving coding efficiency while managing computational complexity through time-distributed processing.
Solution Approach 2:
The patent combines spatial neighboring block motion information with temporal reference picture motion information to create a unified affine merge candidate list. By merging these different sources of motion data, the system achieves more accurate motion prediction and improved coding efficiency without requiring completely separate processing paths, thus controlling overall complexity.
Data Source
AI summary
A video decoding method performed by a decoding device according to the present document is characterized by including: a step for deriving reference subblocks in a reference picture on the basis of the motion vector of an adjacent block on the left side of the current block; a step for deriving a subblock-based temporal merge candidate for the current block on the basis of motion information about the reference subblocks; a step for forming an affine merge candidate list for the current block, the affine merge candidate list including the subblock-based temporal merge candidate; a step for deriving motion information about subblocks of the current block on the basis of the affine merge candidate list; a step for deriving prediction samples for the current block on the basis of the motion information about the subblocks; and a step for generating a reconstructed picture on the basis of the prediction samples.