Video Motion Vector Refinement for Efficient High-Resolution Coding
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Solution Overview
Problem
Current video compression technologies face inefficiencies in coding high-resolution and high-quality video content, particularly in inter prediction, intra prediction, and storage costs, which are exacerbated by the increasing demand for high-definition and ultra-high-definition videos.
Innovation Solution
The method involves adaptively initializing a CABAC context model, refining motion vectors, using unidirectional/bidirectional intra prediction, selectively choosing scan types for transform coefficients, and applying in-loop filtering to virtual blocks with different motion vectors to enhance coding efficiency and video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional video compression technologies are used for high-resolution and high-quality videos, then video quality is maintained, but transmission and storage costs increase due to increased data amount
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting quantization parameters, transformation block sizes, and prediction modes based on local video content characteristics. This allows the encoder to optimize compression ratios while maintaining visual quality, reducing overall data amount without sacrificing perceived video quality.
Solution Approach 2:
The patent introduces dynamic adaptation in video encoding by adjusting encoding parameters in real-time based on content complexity, motion characteristics, and statistical properties of video blocks. This dynamic approach enables more efficient compression compared to static encoding methods, reducing data amount while preserving quality.
2Quantity of substance
If highly efficient video compression technologies are used, then transmission and storage costs are reduced, but coding complexity increases
Solution Approach 1:
The patent segments the video content into different regions or blocks that can be encoded using different parameters and modes. This segmentation allows the encoder to apply complex techniques only where necessary while using simpler methods elsewhere, managing overall coding complexity while achieving efficient compression.
Solution Approach 2:
The patent applies advanced compression techniques selectively to specific video blocks rather than uniformly across the entire frame. By applying complex encoding methods only where they provide significant benefit and using simpler methods elsewhere, the patent reduces overall coding complexity while maintaining compression efficiency.
3Productivity
If existing entropy coding technology is used, then video data is compressed effectively, but coding efficiency can be further improved through adaptive context modeling
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing context model statistics from previously encoded video data. These pre-computed statistics are then used to initialize context models for subsequent encoding, improving compression efficiency without requiring complex real-time calculations during the actual encoding process.
Solution Approach 2:
The patent implements self-service by having the encoder automatically adapt context models based on the statistical properties of the video content being encoded. The system uses its own encoded data to refine and update context models, improving compression efficiency without requiring external intervention or overly complex external control mechanisms.
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.