Video Motion Compensation With Refined Vectors and Adaptive CABAC
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Solution Overview
Problem
Current video compression technologies face challenges in improving coding efficiency, particularly for high-resolution and stereoscopic video content, due to increased data demands and complexities in inter and intra prediction methods.
Innovation Solution
The method involves adaptively initializing a CABAC context model, refining motion vectors, and applying in-loop filtering to enhance coding performance, while using unidirectional or bidirectional prediction techniques for improved compression efficiency and subjective/objective video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video resolution and quality are improved to meet high-definition and ultra-high-definition demands, then video quality is improved, but data amount and transmission/storage costs increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the CABAC context model initialization strategy based on video content characteristics and resolution levels. Different initialization methods are selected for different picture types (I, P, B frames) and resolution levels, optimizing the balance between compression efficiency and video quality without uniformly increasing data amount across all scenarios
Solution Approach 2:
The patent introduces dynamic adaptation in the CABAC context model by using different initialization approaches (reset vs. inheritance from previous picture) based on temporal and spatial characteristics of video content. This dynamic strategy allows the system to maintain high video quality while adapting data compression efficiency to varying content complexity, preventing unnecessary data increase
2Productivity
If inter-picture and intra-picture prediction technologies are used to compress video data, then compression efficiency is improved, but coding complexity increases
Solution Approach 1:
The patent applies local quality by implementing region-specific and block-specific CABAC context modeling within the prediction framework. Different context models are applied to different spatial regions and block types (luma vs. chroma, different prediction modes), allowing efficient compression without uniformly increasing complexity across the entire video stream
Solution Approach 2:
The patent segments the video coding process into multiple independent CABAC context streams that can be independently initialized and managed. This segmentation allows parallel processing of different picture types and regions, improving compression efficiency while distributing computational complexity across multiple manageable contexts rather than one monolithic complex system
3Measurement precision
If CABAC context model is initialized for each picture to ensure coding accuracy, then coding accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by pre-determining the CABAC context initialization strategy based on picture type and video sequence characteristics before actual encoding/decoding. The system pre-selects whether to reset or inherit contexts based on anticipated content characteristics, reducing runtime decision-making and computational overhead while maintaining coding accuracy
Solution Approach 2:
The patent uses copying by inheriting CABAC context states from previously decoded pictures under specific conditions. Instead of always resetting contexts, the system copies proven-effective context states from reference pictures, significantly reducing processing time and computational load while maintaining or improving coding accuracy through experience-based context reuse
Data Source
AI summary
A video encoding/decoding apparatus according to the present invention acquires motion vector refinement information, performs motion compensation on the basis of a motion vector of a current block, refines the motion vector of the current block using at least one or both of the motion vector refinement information and the output of the motion compensation, and performs motion compensation using the refined motion vector.