Image Encoding and Decoding With Overlapped Block Motion Compensation
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Solution Overview
Problem
High-resolution and high-quality image data requires high-efficiency encoding/decoding techniques to reduce the increased costs of transmission and storage due to larger data volumes.
Innovation Solution
The method employs overlapped block motion compensation and candidate lists to improve compression efficiency in image encoding/decoding, using prediction modes, intra prediction modes, and history-based merge candidates to optimize block partitioning and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted or stored using conventional methods, then image quality is maintained, but transmission and storage costs increase due to larger data volumes
Solution Approach 1:
The current block is divided into multiple sub-blocks for independent motion compensation processing. This segmentation allows for more precise local prediction, improving compression efficiency while maintaining image quality by capturing fine-grained motion variations in different regions.
Solution Approach 2:
Different prediction modes and candidate lists are applied to different sub-blocks based on their local characteristics. This local quality approach optimizes compression for each region while preserving overall image quality by adapting to local motion patterns.
2Quantity of substance
If conventional image compression techniques are used, then data volume is reduced, but compression efficiency is insufficient for high-resolution images
Solution Approach 1:
Candidate lists for motion vectors are prepared in advance based on historical and spatial information from previously decoded blocks. This preliminary action enables faster and more accurate motion estimation, improving compression efficiency for high-resolution images without increasing computational complexity during encoding.
Solution Approach 2:
The decoding process uses feedback from previously decoded blocks to refine motion estimation for current blocks. History-based merge candidates and adaptive candidate list updates provide feedback mechanisms that improve compression efficiency by leveraging temporal and spatial correlations in video sequences.
3Device complexity
If simple prediction modes are used, then decoding complexity is reduced, but compression efficiency deteriorates
Solution Approach 1:
The prediction mode selection is made dynamic through adaptive candidate list construction that adjusts based on local image characteristics and motion patterns. This dynamic approach allows the decoder to achieve high compression efficiency by selecting appropriate prediction modes without requiring complex exhaustive searches, as the candidate lists are intelligently pruned based on historical data.
Data Source
AI summary
An image decoding method is disclosed in the present specification. An image decoding method according to the present invention may comprise determining a prediction mode of a current block and performing prediction with respect to the current block on the basis of the determined prediction mode.