Video Motion Vector Prediction Using Merge Candidate Lists
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Solution Overview
Problem
Existing methods for encoding and decoding motion vectors in image compression are inefficient in predicting motion vectors and require improved techniques for accurate prediction and encoding.
Innovation Solution
A method of decoding a motion vector that generates a merge candidate list of neighboring blocks to predict the motion vector in skip or merge modes, using merge difference mode information to determine whether to use a merge motion vector difference, and reconstructing the current block using the determined motion vector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion vectors are encoded using traditional methods without merge candidate lists, then the encoding process is simpler, but the prediction accuracy and compression efficiency deteriorate
Solution Approach 1:
The patent segments the motion vector prediction process by dividing it into distinct stages: generating merge candidate lists from neighboring blocks, selecting base motion vectors from these candidates, calculating motion vector differences, and encoding the differences. This segmentation allows for more accurate prediction while organizing the complexity into manageable, systematic steps that improve overall efficiency
Solution Approach 2:
The patent applies preliminary action by pre-generating merge candidate lists from neighboring blocks before the actual motion vector encoding. These candidate lists are prepared in advance and used as the basis for selecting base motion vectors, which improves prediction accuracy without significantly increasing the complexity during the main encoding process
2Productivity
If merge candidate lists from neighboring blocks are used to predict motion vectors, then prediction efficiency and compression ratio improve, but the encoding and decoding complexity increases
Solution Approach 1:
The patent uses copying by replicating motion vector information from neighboring blocks into merge candidate lists. Instead of performing complex motion estimation for every block, the system copies and reuses motion vectors from spatially or temporally adjacent blocks, significantly improving encoding efficiency while keeping the additional complexity manageable through systematic candidate selection and differential encoding
3Loss of information
If motion vector differential values are used for encoding, then the compression ratio improves, but the precision requirements for differential calculation increase
Solution Approach 1:
The patent applies parameter changes by systematically varying the precision and representation of motion vector differential values based on the specific encoding context. Different differential calculation methods are employed depending on the block size, motion characteristics, and available bits, allowing the system to achieve good compression ratios while adapting precision requirements to match the actual information content rather than using fixed high precision throughout
Data Source
AI summary
Provided is a video decoding method including: generating a merge candidate list including neighboring blocks referred to to predict a motion vector of a current block in a skip mode or a merge mode; when a merge motion vector difference is used according to merge difference mode information indicating whether the merge motion vector difference and a motion vector determined from the merge candidate list are used, determining a base motion vector from a candidate determined among the merge candidate list based on merge candidate information; determining the motion vector of the current block by using the base motion vector and a merge motion vector difference of the current block, the merge motion vector difference being determined by using a distance index and direction index of the merge motion vector difference of the current block; and reconstructing the current block by using the motion vector of the current block.