Modified Merged Affine Model Harmonization for Video Coding Efficiency
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Solution Overview
Problem
Current video coding methods, such as those in the High Efficiency Video Coding (HEVC) standard, face challenges in efficiently handling complex motions like zoom, rotation, and perspective within video compression, leading to suboptimal bandwidth usage and coding efficiency, especially with the increasing demand for higher resolution videos.
Innovation Solution
The proposed solution involves harmonizing affine prediction with other coding tools, including inter-intra prediction, triangular prediction mode, and Ultimate Motion Vector Expression (UMVE), by modifying the merged affine model based on signaled parameters and using weighted sums of predictions to reconstruct video blocks, allowing for more flexible bandwidth management and improved coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video coding methods are used, then bandwidth usage is reduced, but coding efficiency deteriorates when handling complex motions like zoom, rotation, and perspective
Solution Approach 1:
The current video block is divided into multiple sub-blocks, and each sub-block is processed independently with its own motion prediction. This segmentation allows the system to handle complex motions more effectively by applying different prediction modes to different regions, improving coding efficiency without significantly increasing overall bandwidth usage.
Solution Approach 2:
The patent implements dynamic selection of prediction modes (affine, inter-intra, triangular, UMVE) based on the characteristics of each video block. The system adaptsively chooses the most appropriate prediction method for each block, allowing flexible bandwidth management while maintaining high coding efficiency for various motion types.
2Productivity
If affine prediction is used to handle complex motions, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The system dynamically selects from multiple prediction modes (affine, inter-intra, triangular, UMVE) based on block characteristics and motion complexity. Not all modes are applied to all blocks, which reduces the effective complexity while maintaining the ability to handle complex motions when needed.
Solution Approach 2:
Different prediction modes are applied to different sub-blocks or regions based on their local motion characteristics. Simple regions use simpler prediction modes while complex motion regions use more advanced modes like affine or triangular prediction, optimizing the balance between complexity and efficiency.
3Adaptability or versatility
If multiple prediction modes are harmonized, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent creates a unified prediction framework that incorporates multiple prediction modes (affine, inter-intra, triangular, UMVE) within a single system. This multi-functional approach allows the system to adapt to various motion types and block characteristics while managing complexity through standardized processing procedures.
Solution Approach 2:
The system employs dynamic mode selection that adapts to the specific characteristics of each video block. The complexity of each prediction mode is activated only when needed based on motion analysis, allowing high adaptability while keeping the average system complexity manageable through conditional execution.
Data Source
AI summary
The method relates to harmonization between affine mode and other inter coding tools mode. The method for video processing includes acquiring, during a conversion between a current block and a bitstream representation of the current block, an indication of the current block, where the indication indicates whether a merged affine model of the current block should be modified, and performing, at least based on the indication, the conversion between the current block and the bitstream representation of the current block.