Video Decoder Context Model Derivation for Adaptive Loop Filtering
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Solution Overview
Problem
Existing video coding technologies face challenges in improving coding efficiency, enhancing image quality, and reducing processing resource utilization, particularly in the context of cross-component adaptive loop filtering (CCALF) processes.
Innovation Solution
The implementation of an encoder and decoder system that performs a CCALF process by setting flags for adjacent blocks, determining color component indices, deriving context models, and performing entropy encoding and decoding to enable adaptive filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If CCALF process is applied to improve image quality, then image quality is improved, but processing resource utilization increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the CCALF processing based on the third flag and context model. The encoder selectively enables or disables CCALF for different blocks using flag-based control, and the decoder adapts its processing resources accordingly. This allows image quality improvement in regions where CCALF is beneficial while reducing processing resources in regions where it is not needed, resolving the contradiction between image quality and processing resource utilization.
2Productivity
If context-based entropy encoding is used to improve coding efficiency, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent segments the encoding/decoding process by dividing the image into blocks and applying context-based entropy encoding selectively. The first flag, second flag, and third flag create segments that indicate where CCALF should be applied, allowing the context model to be derived and used only in relevant regions. This segmentation approach improves coding efficiency by focusing computational effort on areas that benefit from CCALF while reducing overall device complexity compared to applying context-based encoding uniformly across the entire image.
3Device complexity
If selective CCALF application is implemented to reduce processing resources, then processing resource utilization is reduced, but image quality improvement may be compromised
Solution Approach 1:
The patent implements feedback through the flag system that guides CCALF application. The encoder sets the first flag, second flag, and third flag based on block characteristics, and the decoder uses these flags to determine where to apply CCALF processing. This feedback mechanism ensures that CCALF is applied selectively in regions where it will most improve image quality (such as chroma blocks adjacent to luma blocks) while reducing processing resources in other regions, thus resolving the contradiction between processing resource utilization and image quality improvement.
Data Source
AI summary
A decoder includes circuitry which, in operation, parses a first flag indicating whether a CCALF (cross component adaptive loop filtering) process is enabled for a first block located adjacent to a left side of a current block; parses a second flag indicating whether the CCALF process is enabled for a second block located adjacent to an upper side of the current block; determines a first index associated with a color component of the current block; and derives a second index indicating a context model, using the first flag, the second flag, and the first index. The circuitry, in operation, performs entropy decoding of a third flag indicating whether the CCALF process is enabled for the current block, using the context model indicated by the second index; and performs the CCALF process on the current block in response to the third flag indicating the CCALF process is enabled for the current block.