Look-Up Tables for Video Motion Information Derivation
Solution Overview
Problem
Current video coding technologies face challenges in efficiently compressing higher resolution videos due to increased bandwidth demands, with existing methods struggling to optimize motion information derivation and prediction processes.
Innovation Solution
The use of look-up tables (LUTs) to selectively check and update motion candidates during the motion candidate list construction process for video blocks, enhancing motion information derivation and prediction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional motion candidate list construction methods are used, then the coding process is simpler, but video coding efficiency and compression performance deteriorate for higher resolution videos
Solution Approach 1:
The motion candidate list construction process is segmented into multiple stages: initial candidate list construction, LUT-based candidate selection, and final list assembly. The LUT (look-up table) stores pre-processed motion information from previously coded blocks, allowing the encoder to quickly retrieve and select relevant candidates without processing all possible candidates, thus improving efficiency while managing complexity.
Solution Approach 2:
Motion information from previously coded blocks is pre-processed and stored in LUT structures before the current block encoding. This preliminary action includes deriving motion vectors, reference picture indices, and other motion parameters in advance, so that when encoding the current block, the encoder can directly utilize these pre-computed values without redundant calculations, significantly improving coding efficiency.
2Measurement precision
If motion information from all previously coded blocks is considered, then prediction accuracy improves, but processing time and computational complexity increase
Solution Approach 1:
Instead of uniformly processing motion information from all previously coded blocks, the invention applies local quality by selectively retrieving motion candidates based on spatial and temporal relationships. The LUT structure organizes motion information with different priorities and qualities, allowing the encoder to focus computational resources on the most relevant candidates (e.g., neighboring blocks, temporally correlated blocks) while reducing processing of less relevant blocks, thus achieving high prediction accuracy with reduced processing time.
Data Source
AI summary
Devices, systems and methods for coding video using one or more tables to store motion information and processing subsequent blocks are described. In one aspect, a video coding method is provided to include deriving motion information for a first video block, wherein one or more candidates of one or more tables are selectively checked during a motion candidate list construction process which is used to derive the motion information for the first video block, wherein each table of the one or more tables includes motion candidates derived from previously coded video blocks that are coded prior to the first video block; and coding, based on the motion information, the first video block.