Merge-Mode Motion Vector Averaging for Faster Video Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video coding technologies face challenges in optimizing encoding and decoding processes to efficiently manage increasing digital video data, particularly in selecting appropriate motion vectors and correction processing for prediction images.
Innovation Solution
An encoder and decoder system that derives an average value of motion vector values and registers it as new motion vector information, along with correction processing information, to enhance the prediction candidate list, allowing for improved coding and decoding efficiency by selecting suitable motion vector and correction processing for each block.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional motion vector selection methods are used in H.265/HEVC, then the encoding process is simpler, but coding efficiency deteriorates due to inability to select optimal motion vectors from expanded candidate lists
Solution Approach 1:
The encoder performs preliminary actions by deriving and registering correction processing information alongside motion vector candidates before the actual motion compensation process. This preliminary preparation enables the decoder to efficiently select optimal motion vectors without requiring complex real-time calculations, thus improving coding efficiency while managing encoding complexity.
Solution Approach 2:
Correction processing information acts as an intermediary that bridges the gap between motion vector candidates and final motion compensation. This intermediary element provides additional guidance for selecting optimal motion vectors, enabling better coding efficiency without directly increasing the complexity of the core motion compensation algorithm.
2Reliability
If more prediction candidates are added to the candidate list, then the likelihood of selecting optimal motion vectors increases, but the processing load and time increase
Solution Approach 1:
The invention extracts and separates correction processing information from the main motion compensation process. By deriving this information independently and registering it alongside motion vector candidates, the system enables faster selection of optimal candidates without requiring complex joint optimization, thus maintaining high selection accuracy while reducing processing time.
Solution Approach 2:
Correction processing information is derived and registered in advance as part of the candidate preparation phase. This preliminary action allows the decoder to quickly evaluate and select optimal motion vector candidates without performing additional complex calculations during the decoding phase, thereby reducing processing time while maintaining selection accuracy.
3Manufacturing precision
If correction processing information is derived and registered for each prediction candidate, then coding efficiency improves through better prediction accuracy, but device complexity increases
Solution Approach 1:
The correction processing information serves multiple functions: it guides motion vector selection, improves prediction accuracy, and enables efficient candidate evaluation. By creating this multi-functional element, the system achieves better prediction accuracy without proportionally increasing complexity, as the same information structure serves multiple purposes in the encoding and decoding processes.
Solution Approach 2:
The invention introduces correction processing information as an additional parameter associated with motion vector candidates. This parameter change enables more accurate predictions by providing extra dimensional information for candidate evaluation, while the structured approach to deriving and registering this parameter keeps the increase in device complexity manageable.
Data Source
AI summary
An encoder includes circuitry and memory connected to the circuitry. In operation, the circuitry: derives an average value of motion vector values of two prediction candidates in a prediction candidate list for a merge mode, and registers the average value derived as new motion vector information of a new prediction candidate into the prediction candidate list; and derives new correction processing information regarding correction processing of a prediction image, and registers the new correction processing information derived into the prediction candidate list in association with the new motion vector information.