Adaptive Reference Frame Padding for Video Coding Memory Efficiency
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Solution Overview
Problem
Existing video coding technologies use fixed frame padding areas regardless of reference picture size, leading to inefficient memory usage and suboptimal coding performance.
Innovation Solution
Adaptive determination of frame padding areas based on reference picture size, reducing memory requirements and improving coding efficiency by scaling the padding area according to the reference picture dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed frame padding areas are used for all reference pictures, then coding simplicity is maintained, but memory requirements increase and coding performance becomes suboptimal
Solution Approach 1:
The frame padding area size is made dynamic and adaptive based on reference picture characteristics. The system determines different padding sizes for different reference pictures using formulas that consider picture width, height, and type (e.g., 1/16th of width for inter-coded pictures, 1/8th for intra-coded pictures). This dynamic adaptation resolves the contradiction by optimizing memory usage per reference picture while maintaining or improving coding performance through appropriate padding for each case.
Solution Approach 2:
The invention changes the parameter of frame padding area size from a fixed constant to a variable determined by reference picture attributes. By calculating padding size as a function of picture dimensions and coding type, the system achieves better performance-memory tradeoff. Smaller pictures receive proportionally smaller padding areas, reducing total memory requirements while ensuring adequate padding for accurate motion vector prediction.
2Measurement precision
If larger frame padding areas are used, then motion vector accuracy improves, but memory usage and processing overhead increase
Solution Approach 1:
The padding area size parameter is changed from fixed to adaptive based on reference picture characteristics. By using formulas that calculate padding as a proportion of picture dimensions (e.g., width/16, height/8), the system achieves motion vector accuracy proportional to picture size without uniformly increasing processing overhead for all pictures. This resolves the contradiction by making precision improvement scalable and efficient.
Solution Approach 2:
Different padding area sizes are applied locally to different reference pictures based on their specific characteristics (width, height, coding type). Instead of applying uniform padding to all references, the system tailors padding size to each reference picture's needs, achieving necessary motion vector accuracy for each case while minimizing total processing overhead and memory usage across the entire video sequence.
Data Source
AI summary
The various implementations described herein include methods and systems for coding video. In one aspect, a method includes receiving a video bitstream comprising a plurality of frames and identifying a plurality of reference frames for a current frame of the video bitstream. The current frame has a plurality of blocks, including a current block. The method further includes selecting a reference frame for the current block and determining a frame padding area size for the reference frame. The method also includes reconstructing the current block using the reference frame with a frame padding area having the determined frame padding area size.


