Motion Vector Prediction in Video Encoding Skip and Merge Modes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for encoding and decoding motion information in images face challenges in efficiently performing entropy encoding/decoding, particularly in accurately predicting motion vectors and residual blocks.
Innovation Solution
A method for decoding motion information that determines a prediction mode for a current block as either a skip mode or a merge mode, uses merge candidate information to obtain a base motion vector, and combines this with a merge motion vector difference to determine the motion vector of the current block.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion vector prediction is performed using merge candidate lists in skip mode or merge mode, then the accuracy of motion vector prediction is improved, but the complexity of entropy encoding/decoding increases due to multiple context information requirements
Solution Approach 1:
The patent applies universality by using a single context model for entropy decoding merge candidate information that works across both skip mode and merge mode. Instead of maintaining separate context models for different prediction modes, the invention creates a unified context modeling approach that handles motion vector difference encoding universally, thereby reducing decoder complexity while preserving prediction accuracy.
Solution Approach 2:
The patent applies local quality by selectively applying different context information based on the specific prediction mode and block characteristics. The context model is adapted locally according to the prediction mode (skip or merge) and the position of the current block, allowing optimized entropy decoding performance for different local conditions without requiring complex global context models.
2Manufacturing precision
If multiple context information pieces are used for entropy decoding merge candidate information, then the encoding precision is improved, but the processing time and computational load increase
Solution Approach 1:
The patent extracts only the essential context information needed for entropy decoding merge candidate information, removing redundant context models. By identifying and extracting only the critical context parameters required for accurate decoding, the invention reduces the number of context information pieces from multiple separate models to a streamlined set, thereby decreasing processing time while maintaining encoding precision.
3Measurement precision
If motion vector difference encoding is performed with detailed context information, then the decoding accuracy is improved, but the bitstream complexity and processing overhead increase
Solution Approach 1:
The patent applies preliminary action by pre-defining context model structures and parameters that are prepared in advance for both skip mode and merge mode. The context information is pre-organized and configured before actual entropy decoding occurs, allowing the decoder to efficiently access and apply the appropriate context model without complex runtime decisions, thereby reducing processing overhead while maintaining decoding accuracy.
Data Source
AI summary
Provided is a video decoding method including: determining a prediction mode of a current block to be one of a skip mode and a merge mode; when a motion vector, which is determined from a merge candidate list of the current block, and a merge motion vector difference are to be used, obtaining merge candidate information indicating one candidate in the merge candidate list by performing entropy encoding on a bitstream by applying one piece of context information; determining a base motion vector from one candidate determined from the merge candidate list, based on the merge candidate information; and determining a motion vector of the current block by using a distance index of a merge motion vector difference of the current block and a direction index of the merge motion vector difference to use the base motion vector and the merge motion vector difference.