Motion Refinement Using Weighted Prediction Parameters
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Solution Overview
Problem
Conventional Decoder side Motion Vector Refinement (DMVR) search does not consider bi-prediction parameters and/or weighted prediction parameters, which can affect the accuracy of the search and negatively impact DMVR performance.
Innovation Solution
The proposed solution involves a process that considers prediction parameters such as weighted prediction (WP) parameters or generalized bi-prediction with weighted averaging (BWA) parameters during the DMVR search. This process includes obtaining initial motion vectors, generating modified motion vectors using motion vector offsets, and calculating differences between prediction blocks to determine the best motion vector offset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional DMVR search is performed without considering bi-prediction parameters and weighted prediction parameters, then the search process is simpler and faster, but the accuracy of the search and DMVR performance deteriorate
Solution Approach 1:
The patent applies preliminary action by obtaining bi-prediction parameters and weighted prediction parameters before performing the DMVR search. This allows the search process to incorporate these parameters from the outset, improving search accuracy without requiring complex post-processing or iterative adjustments. The parameters are prepared in advance and used throughout the search to guide motion vector refinement more effectively.
Solution Approach 2:
The patent changes the parameters used in the DMVR search by incorporating bi-prediction parameters (such as motion vectors from both reference pictures) and weighted prediction parameters (weights for combining predictions). These parameter changes enable the search to consider multiple prediction sources and their relative importance, significantly improving search accuracy while managing complexity through systematic parameter integration.
2Manufacturing precision
If bi-prediction parameters and weighted prediction parameters are considered during DMVR search, then the accuracy of prediction blocks is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by obtaining and preparing bi-prediction parameters and weighted prediction parameters before the DMVR search begins. This advance preparation allows the actual search process to use these parameters efficiently without requiring repeated parameter calculations or complex iterative adjustments, thereby improving prediction block accuracy while minimizing the impact on processing speed.
Solution Approach 2:
The patent maintains continuity of useful action by integrating bi-prediction and weighted prediction parameters continuously throughout the DMVR search process. Rather than applying these parameters only at specific stages, the search continuously utilizes all available parameter information to refine motion vectors, ensuring that the full benefit of multiple prediction sources is realized without unnecessary interruptions or re-calculations.
Data Source
AI summary
A method for determining a prediction block for decoding or encoding a current block in a current picture of a video stream. The method includes obtaining a pair of initial motion vectors comprising a first and a second initial motion vector. The method also includes determining whether to refine the initial motion vectors. The step of determining whether or not to refine the initial motion vectors comprises: i) determining whether a first prediction scheme and/or a second prediction scheme is enabled and ii) determining to refrain from refining the initial motion vectors as a result of determining that either the first prediction scheme or second prediction scheme is enabled or determining to refine the initial motion vectors as a result of determining neither the first prediction scheme nor second prediction scheme is enabled.