Adaptive Reference Frame Buffer Partitioning for Video Coding
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Solution Overview
Problem
Conventional video coding systems fail to balance the retention of reference frames effectively, leading to suboptimal coding efficiency in sequences with varying motion levels, as they either retain too many recently coded frames or not enough older frames, which affects prediction quality and compression efficiency.
Innovation Solution
A video coding system dynamically partitions the reference picture cache into long-term and short-term buffer areas based on motion analysis, allocating more space to long-term frames during low motion and short-term frames during high motion, allowing for better prediction matching and improved coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a video coder always keeps a predetermined number of most-recently coded reference frames, then the reference picture cache is managed simply, but coding efficiency deteriorates in sequences with low motion levels
Solution Approach 1:
The patent implements dynamic reference frame retention where the number of reference frames kept in the cache varies based on motion characteristics. The system analyzes motion levels in the video sequence and adjusts the reference frame cache size accordingly - retaining more frames for low-motion sequences and fewer frames for high-motion sequences, thus optimizing coding efficiency while maintaining manageable complexity
Solution Approach 2:
The system changes the parameter of reference frame cache size based on motion analysis. By detecting motion levels in the video content and adjusting the number of reference frames retained, the system adapts to different sequence characteristics, improving compression performance without requiring complex manual configuration
2Productivity
If reference frames are retained older than the Nth most recently coded reference frames, then coding efficiency improves in low motion sequences, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing motion characteristics and making decisions about reference frame retention without external intervention. The motion analysis and adaptive cache management are handled autonomously by the coding system itself, reducing the need for complex external control mechanisms while improving coding efficiency
Solution Approach 2:
The system uses feedback from motion analysis to adjust reference frame retention dynamically. By continuously monitoring motion levels in the video sequence and using this feedback to determine how many reference frames to keep, the system optimizes coding efficiency while maintaining manageable complexity through rule-based adaptation
3Productivity
If younger reference frames are retained within the reference picture cache, then coding efficiency improves in high motion sequences, but loss of older reference frames occurs
Solution Approach 1:
The system dynamically adjusts which reference frames are retained based on motion characteristics. In high-motion sequences, it prioritizes younger reference frames that provide better prediction accuracy, while in low-motion sequences, it retains older frames that may be useful for prediction. This dynamic approach optimizes coding efficiency while minimizing unnecessary loss of reference information
Solution Approach 2:
The system applies different retention strategies to different reference frames based on local conditions. Rather than uniformly retaining or discarding frames, it selectively keeps frames that are most useful for the current coding context, ensuring that the reference picture cache contains frames with the appropriate temporal characteristics for the current motion level
Data Source
AI summary
In a video coding/decoding system, reference picture caches in a video coder and decoder may be partitioned dynamically based on camera and background motion can lead to improved coding efficiency and coding quality. When a camera is fixed and therefore exhibits low motion, a system may allocate larger portions of the reference picture cache to storage of long term reference frames. In this case, foreground elements of an image (for example, a person) may move in front of a relatively fixed background. Increasing the number of long term reference frames can increase the chances that, no matter where the foreground elements are within a frame currently being coded, the reference picture cache will contain at least one frame that provides an adequate prediction match to background elements within the new frame. Thus the background elements uncovered in the current frame can be coded at high quality with a low number of bits. When a camera exhibits high motion, the system may allocate larger portions of the reference picture cache to storage of short term reference frames.