Biprediction Weight Index Derivation for Efficient Image Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, particularly in virtual reality and augmented reality, necessitates a more efficient image/video compression technique to reduce transmission and storage costs.
Innovation Solution
The method involves deriving weight index information for bi-prediction during inter-prediction, specifically using affine merge candidates with control point motion vectors (CPMVs) to generate L0 and L1 prediction samples, and adjusting weight information based on neighboring blocks for improved compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high resolution and high quality image/video are transmitted or stored, then image quality is improved, but transmission and storage costs increase
Solution Approach 1:
The patent applies parameter changes by using weight index information to dynamically adjust the weighting factors in bi-prediction. Instead of using fixed weights, the system varies the weight parameters based on the selected affine merge candidate, allowing for more precise control over prediction accuracy and thereby improving compression efficiency for high-quality image/video
Solution Approach 2:
The patent introduces dynamics by making the weight information adaptive rather than static. The weight index information is derived based on the selected affine merge candidate, allowing the prediction weights to dynamically adjust according to the motion characteristics of different blocks, thereby optimizing compression performance across varying content types
2Measurement precision
If affine merge candidates with control point motion vectors are used for bi-prediction, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining a set of weight index information values associated with different affine merge candidates. This allows the decoder to quickly retrieve and apply appropriate weights without performing complex real-time calculations, thereby maintaining high prediction accuracy while reducing computational complexity during actual decoding operations
Solution Approach 2:
The system uses self-service by deriving weight index information automatically based on the selected affine merge candidate without requiring additional complex processing. The weight information is obtained as a byproduct of the candidate selection process itself, eliminating the need for separate weight optimization computations
Data Source
AI summary
According to the disclosure of the present document, when the inter-prediction type of the current block indicates biprediction, weight index information for a candidate in a merge candidate list or sub-block merge candidate list can be derived, and coding efficiency can be raised.