Hardware-Friendly Motion Field Processing for Video Coding
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Solution Overview
Problem
Current video coding techniques fail to recognize the quality and relationship properties of candidate reference frames, leading to sub-optimal motion vector prediction and inefficient hardware implementation.
Innovation Solution
A method to assign scores to candidate reference frames based on temporal distance, coding quality, and motion prediction characteristics, followed by a scanning order for motion projection, and hardware-friendly designs for motion field hole filling and smoothing to reduce hardware complexity and improve parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed order selection of reference frames is used, then implementation simplicity is maintained, but coding efficiency is sub-optimal
Solution Approach 1:
The patent changes the selection parameter from fixed positional order to dynamic quality-based scoring. Reference frames are selected based on computed scores that consider temporal distance, coding quality metrics, and motion prediction characteristics, allowing the system to adaptively choose the most suitable reference frames rather than following a predetermined selection order.
Solution Approach 2:
The reference frame selection process transitions from static (fixed order) to dynamic (quality-based scoring and ranking). The system continuously evaluates and ranks candidate reference frames based on their current quality metrics and temporal relationships, enabling flexible adaptation to different video content and coding conditions.
2Measurement precision
If comprehensive quality assessment of reference frames is performed, then motion vector prediction quality is improved, but hardware complexity increases
Solution Approach 1:
The quality assessment process is segmented into distinct computable components: temporal distance calculation, coding quality metric evaluation, and motion prediction characteristic analysis. Each component can be implemented as a separate hardware module, allowing for modular implementation that balances assessment comprehensiveness with hardware complexity management.
Solution Approach 2:
Quality metrics and scoring for candidate reference frames are computed in advance during the reference frame selection process, before motion vector prediction is performed. This preliminary assessment allows the system to identify and cache the best reference frames, reducing the computational burden during actual motion prediction operations.
3Manufacturing precision
If motion field hole filling and smoothing operations are performed, then motion prediction accuracy is improved, but hardware bandwidth overhead increases
Solution Approach 1:
The patent extracts and processes only the essential motion field components that require hole filling and smoothing, rather than processing the entire motion field. By identifying and isolating specific regions or vectors that need refinement, the system reduces the overall data volume requiring hardware processing while maintaining prediction accuracy in critical areas.
Data Source
AI summary
Techniques are proposed to improve temporal motion projection in video coding. Candidate reference frames available for use in temporal motion projection are sorted in processing order according to scores assigned based on estimates of the reference frames' suitability for prediction. Such estimates may be based on temporal distance between each candidate reference frame and that reference frame's prediction references. Estimates may be based, for each reference frame, based on an estimate of coding quality of a reference frame from which the respective candidate reference frame makes a prediction reference. Once sorted, the candidate reference frames may be processing in the sorting order to supply prediction data to a current frame that is to be coded from the candidate reference frames. Additionally, hardware friendly designs of motion field hole filling and motion vector smoothing operations are proposed. Such designs can reduce hardware implementation complexity and benefit hardware parallel processing in several aspects: by removing the dependency among different processing block rows for hole filling and motion vector smoothing so that it is becomes easier and friendlier to achieve hardware parallel processing; by reducing the hardware bandwidth loading overhead; by improving hardware pipeline throughput; and/or by avoiding adding a line buffer to store the data from the above row since a line buffer will increase hardware cost.