Video Encoder Motion Vector Prediction Sample Derivation
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Solution Overview
Problem
Existing video encoders face decreased coding efficiency when prediction samples for video partitions are not derived appropriately, leading to increased distortion and processing inefficiencies.
Innovation Solution
An encoder system that includes circuitry and memory to obtain and evaluate motion vector information for different video partitions, reflecting samples to derive prediction samples based on parameter differences, thereby reducing distortion and improving prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If prediction samples are not derived appropriately for video partitions, then coding efficiency decreases, but implementing complex derivation processes increases device complexity
Solution Approach 1:
The patent divides the partition into multiple ranges (first range, second range, third range) and applies different motion vector information to each range based on local characteristics. This segmentation allows the encoder to handle complex motion patterns in different regions independently, improving prediction accuracy without requiring a single complex derivation process for the entire partition.
Solution Approach 2:
The patent applies different motion vector information (first motion vector information, second motion vector information, third motion vector information) to different ranges within the partition based on local motion characteristics. This local quality approach ensures that each range uses the most appropriate motion compensation, improving overall coding efficiency while keeping the derivation logic relatively simple and localized.
2Measurement precision
If motion vector information from different partitions is used to derive prediction samples, then prediction accuracy improves, but processing time increases
Solution Approach 1:
The patent obtains motion vector information from neighboring partitions (second partition, fourth partition) in advance and uses this pre-acquired information to derive prediction samples for the current partition. This preliminary action of gathering motion vector data from surrounding areas before processing the current partition improves prediction accuracy while optimizing the processing sequence to minimize time loss.
Data Source
AI summary
An encoder includes circuitry and memory. The circuitry performs: obtaining first motion vector information of a first partition; obtaining second motion vector information of a second partition; deriving a set of prediction samples for the first partition; and encoding the first partition using the set. When the difference between the motion vector information is not greater than a value, the circuitry reflects a second set of samples to a first set of samples. The first set has been predicted for the first partition using the first motion vector information, and the second set has been predicted for a first range using the second motion vector information. When the difference is greater than the value, the circuitry reflects, to the first set of samples, a third set of samples predicted for a second range larger than the first range using the second motion vector information.


