Overlapped Block Motion Compensation for Blocking Artifact Reduction
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Solution Overview
Problem
Existing video compression technologies face challenges in effectively reducing blocking artifacts and improving coding efficiency, particularly in high-resolution video content, due to limitations in motion compensation techniques.
Innovation Solution
The application of overlapped block motion compensation (OBMC) is enhanced by distinguishing between external and internal OBMC operations, using separate processes for boundary and internal samples within coding units, and employing sub-block level motion compensation to merge blocks with similar motion information, thereby reducing blocking artifacts and enhancing coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional motion compensation is used, then coding efficiency is maintained at current levels, but blocking artifacts remain significant in high-resolution video content
Solution Approach 1:
The patent divides the coding unit into multiple sub-blocks and applies separate motion compensation to each sub-block. This segmentation allows different motion vectors to be used for different regions, reducing blocking artifacts at sub-block boundaries while maintaining coding efficiency through localized motion modeling.
Solution Approach 2:
The patent merges adjacent sub-blocks that share similar motion characteristics into larger prediction units. By combining sub-blocks with comparable motion vectors, the method reduces the number of separate motion compensation operations needed, thereby improving coding efficiency while still preventing blocking artifacts through the merged prediction.
2Object-affected harmful factors
If sub-block level motion compensation is applied to all blocks, then blocking artifacts are reduced, but computational complexity increases significantly
Solution Approach 1:
The patent applies sub-block level motion compensation selectively based on local motion characteristics. Regions with high motion variation receive detailed sub-block processing to reduce blocking artifacts, while regions with uniform motion use coarser prediction. This localized approach reduces overall computational complexity while maintaining artifact reduction where most needed.
Solution Approach 2:
The patent performs full sub-block level motion compensation on only certain coding units or sub-blocks rather than uniformly across the entire video stream. By applying the computationally intensive processing partially—only where motion complexity warrants it—the method reduces blocking artifacts in critical areas while limiting overall computational complexity increases.
3Manufacturing precision
If separate external and internal OBMC operations are performed, then boundary sample quality improves, but processing time increases
Solution Approach 1:
The patent performs external OBMC operations on boundary samples before internal OBMC operations on interior samples. By pre-processing boundary samples with external motion compensation using reference blocks from adjacent coding units, the method ensures high-quality boundary prediction first, then applies internal OBMC only to remaining interior samples, reducing total processing time while maintaining boundary quality.
Data Source
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AI summary
External overlapped block motion compensation (OBMC) may be performed for samples of a coding unit (CU) located along an inter-CU boundary of the CU while internal OBMC may be performed separately for samples located along inter-sub-block boundaries inside the CU. External OBMC may be applied based on substantially similar motion information associated with multiple external blocks neighboring the CU. The external blocks may be treated as a group to provide OBMC for multiple boundary samples together in an external OBMC operation. Internal OBMC may be applied using the same sub-block size used for sub-block level motion derivation. Internal OBMC may be disabled for the CU, for example, if the CU is coded in a spatial-temporal motion vector prediction (STMVP) mode.