Block Prediction Using Temporal Weighting for B-Picture Coding
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Solution Overview
Problem
Conventional moving picture coding systems using B pictures face inefficiencies due to approximated motion vectors and averaging of motion-compensated blocks without considering temporal distances, leading to reduced accuracy and coding efficiency, especially in sequences with fading scenes.
Innovation Solution
A block prediction method that calculates forward and backward motion vectors based on temporal distances and uses weighted interpolation of motion-compensated blocks to improve prediction accuracy and coding efficiency, considering the temporal differences between the current and reference pictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the conventional block prediction method uses approximated motion vectors from co-located blocks in backward reference pictures, then the device complexity is reduced, but the manufacturing precision of the predicted block deteriorates
Solution Approach 1:
The patent changes the parameter of motion vector calculation by considering temporal distance between reference pictures and current picture. Instead of using a fixed approximation method from co-located blocks, the system adjusts motion vector precision based on temporal distance parameters, achieving better accuracy without proportionally increasing complexity.
Solution Approach 2:
The patent applies partial action by selectively increasing motion vector precision only when temporal distance indicates it is necessary. The system calculates more precise motion vectors for blocks where temporal distance suggests higher accuracy needs, while using simpler methods where adequate, thus balancing complexity and precision.
2Ease of operation
If the conventional method averages two motion-compensated blocks without considering temporal distance, then the ease of operation is improved, but the manufacturing precision of the predicted block deteriorates
Solution Approach 1:
The patent introduces temporal distance as a parameter that changes the prediction process. Instead of uniformly averaging blocks, the system adjusts the prediction method based on temporal distance values, achieving higher precision while maintaining operational simplicity through parameter-driven decision making.
Solution Approach 2:
The patent makes the prediction process dynamic by adapting to temporal distance conditions. The system dynamically selects between different prediction approaches (simple averaging vs. more precise methods) based on the temporal distance between reference and current pictures, optimizing accuracy without permanently complicating the operation.
3Device complexity
If the conventional method uses fixed averaging of motion-compensated blocks, then the device complexity is reduced, but the reliability of prediction in fading scenes deteriorates
Solution Approach 1:
The patent uses temporal distance as a key parameter to detect fading scene conditions. When temporal distance indicates a fading scene scenario, the system automatically adjusts the prediction algorithm to use more reliable methods, thereby improving reliability without requiring complex manual intervention or permanent algorithmic complexity.
Data Source
AI summary
In the method for predicting an image, a current image block is predicted using first and second image blocks, temporal information for a current picture and at least one reference picture related to one of the first and second image blocks.