Adaptive Reference Frame Management for Video Coding Quality
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video coding methods suffer from error propagation due to the use of fixed reference frames, leading to lower coding quality, particularly as the coding process progresses.
Innovation Solution
Implement adaptive long-term reference frame management based on coding quality and frame type analysis, updating the reference frame dynamically to improve coding quality by selecting frames with higher quality and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed reference frame is used in video coding, then the coding process is simple and efficient, but error propagation occurs leading to lower coding quality
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a fixed reference frame to a dynamic reference frame selection mechanism. The system dynamically selects reference frames based on coding quality metrics and frame type analysis, allowing the reference frame to change adaptively during the coding process. This resolves the contradiction by maintaining coding efficiency while preventing error propagation through intelligent reference frame management.
Solution Approach 2:
The patent implements feedback by continuously monitoring coding quality and using this information to adjust reference frame selection. The system obtains coding quality of the current coded frame and uses this feedback to determine whether to update the long-term reference frame, creating a closed-loop control mechanism that maintains high coding quality while preserving efficiency.
2Manufacturing precision
If the reference frame is updated frequently to improve coding quality, then coding accuracy improves, but the complexity of the coding process increases
Solution Approach 1:
The patent applies parameter changes by modifying the reference frame selection parameters based on coding quality metrics and frame type analysis. Instead of using a fixed reference frame, the system changes the reference frame parameter dynamically based on calculated coding quality and motion vector analysis, achieving high coding accuracy without excessive complexity.
Solution Approach 2:
The system implements self-service by automatically evaluating coding quality and making decisions about reference frame updates without external intervention. The coding device autonomously determines when to update the long-term reference frame based on internal quality metrics, reducing the need for complex external control mechanisms while maintaining high coding accuracy.
3Reliability
If coding quality metrics are calculated for every frame to improve reference frame selection, then coding quality improves, but processing time increases
Solution Approach 1:
The patent applies partial action by calculating coding quality metrics selectively rather than exhaustively for every frame. The system uses motion vector information and frame type analysis to determine when coding quality calculation is necessary, avoiding unnecessary processing while maintaining high coding quality where it matters most.
Solution Approach 2:
The patent implements preliminary action by using motion vector analysis and frame type determination as preparatory steps before calculating coding quality. This preliminary classification allows the system to make informed decisions about when full coding quality calculation is needed, reducing overall processing time while maintaining coding quality.
Data Source
AI summary
A method, apparatus, and computer-readable storage medium for coding multimedia data with adaptive reference frame management. The method codes a current multimedia frame using a corresponding long-term reference frame to obtain a current coded multimedia frame. Coding quality is obtained for the long-term reference frame and calculated for the current coded multimedia frame. The type of the current coded multimedia frame is determined based on motion vectors of its coding blocks. The long-term reference frame is updated based on the coding quality of both frames and the frame type. Subsequent multimedia frames are then coded using the updated long-term reference frame, enabling improved coding efficiency through intelligent reference frame adaptation.