Motion Candidate LUT Ordering for Efficient Video Coding
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Solution Overview
Problem
Existing video coding standards face challenges in efficiently handling high-resolution video due to increased bandwidth demand and complexity, particularly in managing motion candidates during encoding and decoding processes.
Innovation Solution
The use of look-up tables (LUTs) to derive and adaptively change the insertion order of motion candidates, facilitating improved conversion between video blocks and bitstream representations, which can be implemented in existing and future video coding standards like HEVC.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional motion candidate handling methods are used in existing video coding standards, then the encoding and decoding processes can be implemented with current complexity levels, but compression performance and coding efficiency are insufficient for high-resolution video
Solution Approach 1:
The motion candidate list is segmented into multiple groups or categories (e.g., spatial candidates, temporal candidates, combined candidates) with different insertion priorities. This segmentation allows the encoder to process and transmit only the most relevant candidates first, improving compression efficiency without requiring complete reprocessing of all candidates, thus managing computational complexity better.
Solution Approach 2:
Motion candidates are pre-organized and prioritized in a predetermined insertion order based on their expected importance and likelihood of being selected. This preliminary arrangement reduces the computational burden during encoding and decoding by avoiding dynamic reevaluation of candidate priorities, thereby improving coding efficiency while controlling complexity.
2Adaptability or versatility
If motion candidates are processed in a fixed insertion order, then the encoding and decoding processes are simpler to implement, but coding efficiency is reduced due to inability to adapt to different video content characteristics
Solution Approach 1:
The insertion order of motion candidates is made dynamic rather than fixed. The order can be adjusted based on video content characteristics, such as motion patterns, scene changes, or block types. This dynamic adaptation improves coding efficiency by prioritizing relevant candidates for specific content types while maintaining manageable complexity through predefined adjustment rules.
Solution Approach 2:
The insertion order parameter of motion candidates is changed adaptively based on video content analysis. Different parameters such as candidate source (spatial/temporal), motion magnitude, or block position can influence the insertion order. This parameter-based adaptation enables the system to respond to diverse video content while keeping the underlying processing framework relatively simple.
3Productivity
If all motion candidates are transmitted and processed equally, then completeness of motion information is maintained, but bandwidth usage increases and processing efficiency decreases
Solution Approach 1:
Only the most relevant motion candidates are extracted and transmitted based on predetermined criteria and insertion order. Less important candidates are either omitted or given lower priority, reducing the quantity of data that needs to be transmitted and processed. This extraction approach maintains essential motion information while reducing bandwidth consumption and improving processing efficiency.
Solution Approach 2:
Different motion candidates are treated with different levels of importance or quality based on their local relevance to the current block being encoded. Candidates from regions with similar motion characteristics or higher prediction accuracy are given higher priority and transmitted with more detail, while less relevant candidates receive reduced treatment. This local quality differentiation optimizes bandwidth usage by focusing resources on the most important motion information.
Data Source
AI summary
Devices, systems and methods for encoding and decoding digital video using a look-up tables (LUTs) containing motion candidates are described. A method of video processing includes maintaining one or more tables, at least one table of the one or more tables is associated with one or more entries, deriving, based on a first set of motion candidates in the at least one table, a second set of motion candidates, and performing, based on the second set of motion candidates, a conversion between a current block of a video and a bitstream representation of the video.