Block-Based In-Loop Filtering With Adaptive Filter Index Selection
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Solution Overview
Problem
Existing image encoding and decoding technologies face challenges in reducing the size of buffers required for storing residual and prediction samples during in-loop filtering, particularly with advancements in hardware and AI technology.
Innovation Solution
An image decoding and encoding method that determines a filter index for in-loop filtering based on representative values of current and neighboring blocks, allowing adaptive selection of in-loop filter sets to optimize filtering processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If in-loop filtering is performed using residual samples and prediction samples in addition to reconstructed samples, then image quality is enhanced, but buffer size requirements increase
Solution Approach 1:
The patent extracts only the necessary information (filter index) from the residual and prediction samples rather than storing the complete sample data. By deriving filter indices from representative values of these samples and using those indices to select filtering parameters, the system achieves enhanced image quality through adaptive filtering while significantly reducing buffer requirements compared to storing full residual and prediction sample arrays.
2Adaptability or versatility
If multiple in-loop filter sets are maintained for different blocks, then filtering adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic adaptability by calculating filter indices based on representative values from residual and prediction samples of current and neighboring blocks. Instead of maintaining multiple static filter sets, the system dynamically selects appropriate filtering parameters by computing indices that reflect local block characteristics, achieving high filtering adaptability while avoiding the complexity of storing and managing multiple complete filter sets.
Solution Approach 2:
The patent changes the parameter representation from storing complete filter sets to storing compact filter indices. By representing filtering configurations as indices derived from block representative values, the system achieves versatile adaptive filtering capability while significantly reducing the complexity associated with managing multiple full filter sets. The filter index serves as a compact parameter that references optimal filtering configurations.
Data Source
AI summary
Provided are an image decoding method and apparatus and an image encoding method and apparatus. An image decoding method includes obtaining a first representative value of a current block with respect to residual samples of the current block or prediction samples of the current block, and obtaining a second representative value of each of neighboring blocks with respect to residual samples of each of the neighboring blocks of the current block or prediction samples of each of the neighboring blocks of the current block. The method includes obtaining a filter index indicating one in-loop filter set among a plurality of in-loop filter sets, based on the first representative value and the second representative value, and performing in-loop filtering on the current block, based on the one in-loop filter set determined by the filter index.