Motion Vector Resolution Ordering With Template Matching for Video Coding
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in reducing redundancy and optimizing motion vector resolution, particularly in intra and inter-picture prediction, leading to suboptimal compression ratios and increased bandwidth requirements.
Innovation Solution
The implementation of adaptive motion vector resolution (AMVR) using an adaptive order of motion vector resolutions (MVRs) and template matching (TM) to determine the most efficient motion vector predictors, allowing for more precise and efficient video encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If uncompressed video is used, then video quality is maintained, but bandwidth and storage requirements become excessively high
Solution Approach 1:
The patent applies parameter changes by varying the motion vector resolution (MVR) parameter across different coding blocks. Instead of using a fixed resolution for all motion vectors, the system dynamically adjusts the MVR parameter based on the complexity and motion characteristics of each block, thereby reducing overall data requirements while maintaining quality where needed
Solution Approach 2:
The patent implements local quality by applying different motion vector resolutions to different coding blocks within a picture. Blocks with complex motion patterns receive higher resolution motion vectors, while blocks with simple or static content use lower resolution, optimizing the balance between quality and compression efficiency locally across the video frame
2Quantity of substance
If compression is applied to reduce bandwidth and storage, then data requirements decrease, but coding complexity increases
Solution Approach 1:
The patent applies dynamics by making the motion vector resolution adaptive rather than fixed. The system dynamically selects the appropriate MVR level for each coding block based on its motion characteristics, allowing the encoder to adjust complexity levels dynamically during encoding to optimize the compression-performance tradeoff
Solution Approach 2:
The patent applies segmentation by dividing the video picture into multiple coding blocks and applying different motion vector resolutions to each block independently. This segmentation allows the system to manage complexity at the block level rather than throughout the entire frame, reducing overall coding complexity while maintaining compression efficiency
3Ease of manufacture
If fixed motion vector resolution is used, then implementation is simple, but compression efficiency is suboptimal
Solution Approach 1:
The patent changes the motion vector resolution parameter from a fixed value to a variable parameter that can take multiple discrete resolution levels. This parameter change enables the system to achieve higher compression efficiency by selecting appropriate resolution levels for different blocks while maintaining relatively simple implementation through standardized resolution options
Data Source
AI summary
Aspects of the disclosure provide a method and an apparatus for video decoding. The apparatus includes processing circuitry that decodes prediction information of a current block in a current picture. The prediction information indicates that an adaptive motion vector prediction (AMVP) mode is applied to the current block with an adaptive motion vector resolution (AMVR) mode. The prediction information indicates motion information. The processing circuitry determines a respective first motion vector predictor (MVP) for each of a first plurality of motion vector resolutions (MVRs) corresponding to a first reference picture based on the motion information and the respective first MVR in the first plurality of MVRs. The processing circuitry perform template matching (TM) by determining TM costs based at least on the first plurality of MVRs and the first MVPs. The processing circuitry generates an adaptive order of the first plurality of MVRs based on the TM costs.