Unified Context Model for Video Coding Redundancy
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Solution Overview
Problem
Current video coding technologies face challenges in efficiently reducing redundancy in video signals, particularly in representing less likely intra prediction directions and motion vectors, which affects compression efficiency and bandwidth requirements.
Innovation Solution
The proposed solution involves a method for video encoding and decoding that uses multiple context models and context incremental indices to determine the current context model for decoding syntax elements, allowing for efficient representation of both intra and inter prediction modes, including the use of merge modes and motion vector prediction techniques to reduce redundancy in the bitstream.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional video coding techniques are used to represent intra prediction directions and motion vectors, then the bitstream size increases, but compression efficiency decreases
Solution Approach 1:
The patent combines the context models for intra prediction direction and motion vector representation into a unified context model. This merging allows shared probability estimates and context states to be used across both syntax element types, reducing the overall bitstream size while maintaining compression efficiency through coordinated encoding of related prediction parameters
Solution Approach 2:
The unified context model serves multiple functions by handling both intra prediction direction coding and motion vector coding. This multi-functional approach allows the same context modeling mechanism to optimize representation for different types of prediction syntax elements, improving overall compression efficiency without requiring separate specialized models for each parameter type
2Measurement precision
If multiple context models are used to represent different prediction directions and motion vectors, then the representation accuracy improves, but the device complexity increases
Solution Approach 1:
Multiple specialized context models are merged into a single unified context model that can adaptively represent different prediction directions and motion vectors. This consolidation reduces device complexity by eliminating the need to manage multiple separate context models while maintaining representation accuracy through unified probability estimation and context state management across all prediction types
Data Source
AI summary
Aspects of the disclosure provide a method and an apparatus for video coding. In some examples, an apparatus includes processing circuitry that receives a bitstream that includes coded information representing a current bin of a current syntax element of a first syntax element type for a block in a picture. The processing circuitry determines, for the current bin of the current syntax element, a current context model associated with both the first syntax element type and a second syntax element type different from the first syntax element type. The processing circuitry also decodes the coded information according to the current context model to obtain the current bin of the current syntax element, and reconstructs the current block according to a characteristic indicated by the current bin of the current syntax element.