Adaptive Reference Line Filtering for Intra Image Prediction
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Solution Overview
Problem
The increasing resolution and quality of high-definition and ultra-high-definition images result in higher data volumes, leading to increased costs in transmission and storage, necessitating improved image compression techniques.
Innovation Solution
The method involves configuring multiple reference sample lines for intra prediction, with adaptive padding and filtering based on block characteristics, to enhance compression efficiency during image encoding and decoding.
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 increasing data volumes
Solution Approach 1:
The patent changes parameters of reference samples by applying adaptive filtering operations. The filtering strength and type are adjusted based on local image characteristics (variance, gradient), transforming reference sample parameters to optimize prediction accuracy while maintaining compression efficiency
Solution Approach 2:
The patent introduces dynamic adaptation in the intra-prediction process by selectively applying different filtering operations based on local image characteristics. The filtering is not static but adapts to local variance and gradient properties, enabling the system to respond dynamically to different image regions
2Device complexity
If conventional intra-prediction methods are used without adaptive filtering, then device complexity is reduced, but compression efficiency deteriorates due to inability to handle diverse local image characteristics
Solution Approach 1:
The patent applies different filtering operations to different reference sample lines based on local image characteristics. Each reference sample line may receive different filtering treatment (strong, weak, or no filtering) depending on its local variance and gradient properties, achieving local optimization without uniform complexity
Solution Approach 2:
The patent segments the reference sample lines into different groups based on their local characteristics. Reference samples are divided into those requiring strong filtering, weak filtering, or no filtering, allowing differentiated processing that balances complexity and efficiency
Data Source
AI summary
An image encoding/decoding method and apparatus for performing intra prediction using a plurality of reference sample lines are provided. An image decoding method may comprise configuring a plurality of reference sample lines, reconstructing an intra prediction mode of a current block, and performing intra prediction for the current block based on the intra prediction mode and the plurality of reference sample lines.