Dense Motion Vector Interpolation for Blocking Artifact Reduction
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Solution Overview
Problem
Existing video encoding methods using block-based motion estimation and compensation suffer from inaccuracies and blocking artifacts due to the limited number of motion vectors transmitted, leading to inefficient coding and poor prediction quality.
Innovation Solution
Employing two different motion vector interpolation methods on a picture segment basis, with interpolation information signaled using a binary flag, allowing content-adaptive selection and reducing computational complexity without additional signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If block-based motion estimation and compensation is used with limited motion vectors, then device complexity is reduced, but manufacturing precision deteriorates due to blocking artifacts and inaccuracies
Solution Approach 1:
The picture is divided into multiple interpolation segments, each processed with its own motion interpolation method. This segmentation allows different regions to use different reconstruction approaches, improving overall accuracy without uniformly increasing complexity across the entire picture.
Solution Approach 2:
Different motion interpolation methods are applied to different segments based on local characteristics. This enables higher precision in regions requiring it while maintaining lower complexity in other regions, resolving the contradiction between overall complexity and local accuracy.
2Manufacturing precision
If more motion vectors are transmitted to improve reconstruction accuracy, then manufacturing precision improves, but loss of information decreases (more information transmitted), increasing device complexity and bitstream overhead
Solution Approach 1:
Motion interpolation methods serve as intermediaries to reconstruct the dense motion field from sparse motion vectors. Instead of transmitting all motion vectors, the interpolation methods mathematically derive the missing information, reducing transmitted data while maintaining reconstruction accuracy.
Solution Approach 2:
The patent changes the parameter representation by using interpolation methods (mathematical models) to represent motion field information more efficiently. Instead of transmitting raw motion vectors for all blocks, it transmits fewer vectors plus interpolation method indicators, reducing overall data complexity.
3Adaptability or versatility
If block-based prediction with hierarchic splitting is applied, then adaptability improves for different content, but object-generated harmful factors increase due to blocking artifacts
Solution Approach 1:
The patent introduces dynamic selection of interpolation methods for different segments, allowing the system to adapt to local motion characteristics. This dynamic approach reduces blocking artifacts by using more appropriate interpolation techniques in regions where block-based methods fail, while maintaining content adaptability.
Data Source
AI summary
A sparse motion field exchanges motion information between encoder and decoder. Side information indicates a suitable interpolation approach for interpolating the motion vectors of the dense motion field different from the signaled sparse motion field motion vectors. The side information is provided on a segment basis. The segments are derived at the encoder side and the decoder side similarly, based on the reference images and the sparse motion field.