Video Encoding Resolution-Aware Motion Vector Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional video encoding methods, such as H.264/H.265, encode video frames indiscriminately, leading to poor video quality at limited bandwidth, as they do not effectively manage varying frame resolutions, resulting in suboptimal encoding and decoding accuracy.
Innovation Solution
A method and apparatus that determine a target motion vector for each block in a current frame at a specific resolution, calculate motion vector predictions, and encode frames based on motion vector differences, incorporating resolution information to improve encoding accuracy and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all video frames are encoded indiscriminately, then encoding completeness is maintained, but video quality deteriorates at limited bandwidth
Solution Approach 1:
The patent applies different encoding strategies to different video frames based on their resolution characteristics. High-resolution frames use one encoding approach while low-resolution frames use another, optimizing quality for each frame type rather than applying a uniform encoding method to all frames.
Solution Approach 2:
The patent dynamically changes encoding parameters based on frame resolution. By detecting whether a frame is high or low resolution, the system adjusts motion vector precision and encoding depth accordingly, improving overall video quality within bandwidth constraints.
2Measurement precision
If conventional encoders encode all frames uniformly, then encoding simplicity is maintained, but encoding accuracy deteriorates
Solution Approach 1:
The patent introduces dynamic encoding where the encoder adapts its behavior based on frame characteristics. The encoding process transitions from static uniform encoding to dynamic resolution-aware encoding, improving accuracy while managing complexity through automated detection and adaptation.
Solution Approach 2:
The patent segments the video stream into high-resolution and low-resolution frame groups, applying different encoding algorithms to each segment. This segmentation allows the system to achieve higher encoding accuracy for critical high-resolution frames while using simpler encoding for low-resolution frames.
3Measurement precision
If motion vectors are calculated at full resolution, then motion estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies different motion vector calculation resolutions to different frame types. High-resolution frames receive full-resolution motion estimation for accurate motion compensation, while low-resolution frames use reduced-resolution motion estimation, optimizing the balance between accuracy and computational load.
Data Source
AI summary
A video coding method includes: obtaining a current frame from a plurality of video frames to be encoded, the plurality of video frames having different resolutions; determining a target motion vector (MV) corresponding to each block in the current frame at a target resolution represented by selected target MV resolution information; obtaining a motion vector prediction (MVP) corresponding to each block and at the target resolution; and encoding the current frame according to a motion vector difference (MVD) between each target MV and the MVP of each block to obtain encoded data. The encoded data includes identification information representing the target resolution.