Image Signal Decoding With Split Prediction Unit Motion Derivation
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Solution Overview
Problem
Existing video encoding and decoding methods face challenges in efficiently partitioning coding blocks and deriving motion information, limiting inter-prediction efficiency.
Innovation Solution
The method involves partitioning a coding block into multiple prediction blocks and deriving motion information for each block using an inter-region motion information table, enhancing inter-prediction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion information is separated into list 0 and list 1 for different prediction units, then motion information accuracy is improved, but coding complexity increases
Solution Approach 1:
The patent segments motion information into two separate lists (list 0 and list 1) corresponding to different prediction units within a coding block. This segmentation allows independent processing and optimization of motion information for each prediction unit, improving motion estimation accuracy while managing complexity through structured organization
Solution Approach 2:
The patent dynamically determines whether to divide a coding block into multiple prediction units based on picture type, block size, and other factors. The partitioning is not fixed but adapts to different coding scenarios, allowing the system to optimize between accuracy and complexity on a per-block basis
2Measurement precision
If a coding block is divided into multiple prediction units, then prediction accuracy is improved, but processing overhead increases
Solution Approach 1:
The coding block is segmented into multiple prediction units (first and second prediction units) with separate motion information lists. This segmentation enables more precise motion compensation by allowing different motion vectors to be applied to different regions, improving prediction accuracy
Solution Approach 2:
The patent changes the parameter of motion information organization by creating separate lists (list 0 and list 1) for different prediction units. This parameter change allows the system to optimize prediction accuracy by selecting the most appropriate motion information for each region while managing processing overhead through structured data organization
3Manufacturing precision
If separate motion information lists are used for different prediction units, then encoding precision is improved, but data structure complexity increases
Solution Approach 1:
Motion information is segmented into separate lists (list 0 and list 1) for different prediction units. This segmentation improves encoding precision by allowing independent optimization of motion vectors for each prediction unit while maintaining a structured and manageable data organization scheme
Solution Approach 2:
The data structure dynamically adapts based on whether a coding block is divided or not. When division is not performed, a single motion information list is used, simplifying the data structure. When division is performed, separate lists are created, improving precision. This dynamic structure optimizes between precision and complexity
Data Source
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AI summary
A method for decoding an image, according to the present invention, comprises the steps of: determining whether a coding block is divided into a first prediction unit and a second prediction unit; determining a partition type of the coding block when determining that the coding block is divided; deriving first motion information about a first prediction unit and second motion information about a second prediction unit within the coding block; and acquiring a prediction sample within the coding block on the basis of the first motion information and the second motion information.