Intra Coding Sub-Mode Similarity Evaluation for Predictor Diversity
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Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently reducing redundancy within video frames, leading to sub-optimal compression efficiency due to similarities between different prediction modes or sub-modes.
Innovation Solution
Implementing a method to evaluate similarities between different intra coding modes by comparing derived parameters, allowing for modification or replacement of sub-modes to enhance predictor diversity and improve compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the same predictor generation method is used for multiple intra coding sub-modes, then the coding process is simplified, but predictor diversity is reduced leading to sub-optimal compression efficiency
Solution Approach 1:
The patent segments the intra coding process by introducing separate predictor generation methods for different sub-modes. Specifically, it divides the prediction process into DIMD-based predictors for certain sub-modes and TIMD-based predictors for others, allowing each segment to be optimized independently for better compression efficiency while maintaining manageable complexity through modular organization
Solution Approach 2:
The patent implements dynamic selection of predictor generation methods based on the specific sub-mode being used. The system dynamically switches between DIMD and TIMD approaches depending on the intra coding sub-mode, enabling adaptability that improves compression efficiency without requiring manual configuration or complex static design
2Productivity
If predictor diversity is increased by using different generation methods for sub-modes, then compression efficiency improves, but the complexity of the coding process increases
Solution Approach 1:
The patent merges two existing predictor generation techniques (DIMD and TIMD) into a unified intra coding framework. By combining these methods and assigning them to different sub-modes respectively, the system achieves enhanced predictor diversity and improved compression efficiency while leveraging the strengths of both approaches without requiring entirely new complex mechanisms
3Loss of substance
If redundancy within video frames is reduced through better prediction modes, then bitstream size decreases, but the complexity of evaluating and selecting optimal modes increases
Solution Approach 1:
The patent applies preliminary action by pre-defining specific predictor generation methods for specific sub-modes. This预先 assignment eliminates the need for complex real-time evaluation and selection processes, as the optimal predictor method is predetermined based on the sub-mode, thereby reducing bitstream size through efficient prediction without incurring high evaluation complexity
Data Source
AI summary
Predictor generation for a first prediction sub-mode may substantially be the same as another prediction sub-mode. Similarities between the two prediction sub-modes may be evaluated by comparing parameters derived in sub-mode selection. A coder may, based on evaluation results, modify or replace one of the prediction sub-modes for processing a current block of content.