Intra Prediction Sub-Block Offsets for Lower Video Data Volume
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Solution Overview
Problem
The increasing demands for high-resolution and high-quality images, particularly stereographic content, lead to higher data volumes, resulting in increased costs for transmission and storage, necessitating more efficient video signal encoding and decoding methods.
Innovation Solution
A method and device for encoding and decoding video signals that hierarchically partition coding blocks into sub-blocks, determining offsets for each sub-block based on intra prediction patterns, and updating prediction samples using offsets derived from adjacent reference samples.
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 improved, but transmission and storage costs increase
Solution Approach 1:
The current block is divided into multiple sub-blocks, and intra prediction is performed separately for each sub-block. This segmentation allows for more precise local prediction, improving compression efficiency while maintaining high image quality, thereby reducing the data volume required for transmission and storage.
Solution Approach 2:
Different prediction modes and offset corrections are applied to different sub-blocks based on their local characteristics. This local quality approach ensures that each region is predicted with the most appropriate method, improving overall compression performance without sacrificing image quality, thus reducing redundant data.
2Measurement precision
If conventional intra prediction is performed on the entire current block, then processing is simplified, but prediction accuracy decreases
Solution Approach 1:
The current block is divided into multiple sub-blocks for separate prediction processing. This segmentation improves prediction accuracy by capturing local variations, while the systematic approach to sub-block processing keeps the increased complexity manageable through reuse of reference samples and standardized offset calculation methods.
Solution Approach 2:
The patent introduces offset values that are added to prediction samples to correct prediction errors. By changing the parameter space to include these offset corrections, the prediction accuracy is enhanced without requiring completely new processing architectures, thus managing complexity while improving precision.
3Measurement precision
If prediction samples are corrected using offsets derived from reference samples, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
Reference samples are collected and prepared in advance from neighboring blocks and lines. These pre-computed reference samples are then used to generate offset values for correcting prediction samples. This preliminary action reduces the computational burden during the main prediction process, improving accuracy while managing energy consumption.
Solution Approach 2:
The prediction system uses its own reference samples (derived from previously processed areas of the same image) to generate correction offsets. This self-service approach allows the system to improve its own prediction accuracy using information already available in the data stream, minimizing the need for external computational resources.
Data Source
AI summary
Provided is a method for decoding a video signal. The method includes generating a first prediction sample by performing intra prediction on a current block, determining an intra prediction pattern of a current block, partitioning the current block into a plurality of sub-blocks based on the determined intra prediction pattern, generating a first prediction sample for a sub-block by performing intra prediction, determining an offset for the sub-block to obtain a second prediction sample, and generating the second prediction sample for the sub-block by using the first prediction sample and the offset.