Segmented Video Block Prediction Using IBC and Intra Modes
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Solution Overview
Problem
Existing video coding technologies, such as AV1, HEVC, and VVC, face challenges in efficiently segmenting and predicting video blocks for optimal compression, particularly in handling diverse video content characteristics.
Innovation Solution
A content-adaptive segmented prediction mode is introduced, where blocks are segmented into multiple segments, with different prediction modes applied to each segment, including intra block copy and intra prediction modes, and threshold-based segmentation is used to determine segment boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single prediction mode is used for the entire block, then the device complexity is reduced, but the prediction accuracy deteriorates for diverse video content
Solution Approach 1:
The current block is divided into multiple segments (first segment and second segment), allowing different prediction modes to be applied to each segment. This segmentation enables the system to handle diverse video content characteristics within different regions of the same block, improving overall prediction accuracy without requiring complex analysis of the entire block at once.
Solution Approach 2:
Different prediction modes are assigned to different segments based on their local content characteristics. The first segment uses intra block copy mode while the second segment uses intra prediction mode, allowing each segment to be optimized for its specific content type rather than applying a uniform approach across the entire block.
2Productivity
If multiple prediction modes are applied to different segments, then the compression efficiency is improved, but the processing complexity increases
Solution Approach 1:
The block is segmented into multiple regions that can be processed using different prediction modes simultaneously. This allows the encoder to explore multiple compression strategies in parallel across different segments, improving overall compression efficiency while distributing the processing complexity across manageable segments rather than requiring complex sequential processing.
Solution Approach 2:
The patent applies prediction modes to segments rather than requiring full analysis of all possible modes for the entire block. This partial action approach allows the system to achieve good compression results by applying appropriate prediction modes to relevant segments without exhaustively processing the entire block with all possible modes, thus improving efficiency while controlling complexity.
3Adaptability or versatility
If threshold-based segmentation is used to determine segment boundaries, then the adaptability to content variations is improved, but the processing time increases
Solution Approach 1:
The patent uses threshold values to dynamically determine segment boundaries based on content characteristics. By changing the parameter (threshold) that defines segment boundaries, the system can adapt to different content variations automatically. This allows the segmentation to be flexible and content-adaptive without requiring manual configuration or complex analysis, thus improving adaptability while keeping processing time manageable.
Data Source
AI summary
Systems and methods for content-adaptive segmented prediction mode are provided. A method includes receiving a picture, and encoding the picture, the encoding including predicting a current block of the picture. The predicting includes: segmenting samples within the current block into a plurality of segments including a first segment and a second segment; predicting the first segment of the current block of the picture by using a first prediction mode that is an intra block copy (IBC) mode; and predicting the second segment of the current block of the picture by using a second prediction mode, different from the first prediction mode, that is an intra prediction mode that uses neighboring reconstructed samples to perform intra prediction.