LMCS Luma Mapping and Chroma Scaling for Dual-Tree Video Coding
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality image/video data, particularly in immersive media formats like VR and AR, leads to higher transmission and storage costs due to increased data volume, necessitating a more efficient compression technology.
Innovation Solution
Implementing a method and apparatus for luma mapping with chroma scaling (LMCS) that includes efficient filtering, constrained LMCS codewords, linear mapping, and simplified index derivation procedures, allowing for improved image coding efficiency and reduced computational complexity, even in dual tree structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If luma mapping with chroma scaling (LMCS) is applied to improve compression efficiency and visual quality, then compression efficiency and visual quality are improved, but computational complexity increases
Solution Approach 1:
The patent applies parameter changes by modifying the LMCS process through constrained codeword ranges, linear mapping functions, and simplified scaling factor derivations. These parameter modifications reduce the computational burden while preserving the core functionality of improving compression efficiency and visual quality.
Solution Approach 2:
The patent extracts and simplifies complex computational steps from the full LMCS process. By removing unnecessary calculations and retaining only the essential operations for achieving compression efficiency and visual quality improvement, the computational complexity is reduced while maintaining the beneficial effects.
2Measurement precision
If high-resolution, high-quality image/video data is transmitted to meet demand for 4K/8K UHD and immersive media, then visual quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent changes the parameter of data representation through LMCS, transforming the way image/video data is encoded and transmitted. This parameter change enables maintaining high visual quality while reducing the amount of data that needs to be transmitted and stored, thereby reducing transmission cost and storage cost.
Solution Approach 2:
The patent applies local quality by differentiating the processing of luma and chroma components, and by applying selective scaling factors to different regions of the image/video data. This allows maintaining high visual quality in important regions while reducing data volume in less critical areas, balancing quality and cost.
3Measurement precision
If complex filtering and processing operations are applied to improve visual quality, then subjective and objective visual quality are improved, but processing time and computational resources increase
Solution Approach 1:
The patent extracts and removes time-consuming filtering operations from the processing pipeline, retaining only the essential operations that contribute to visual quality improvement. This extraction reduces processing time while maintaining the beneficial effects on subjective and objective visual quality.
Solution Approach 2:
The patent applies preliminary action by pre-computing scaling factors and mapping parameters that can be quickly applied during actual processing. This preliminary preparation reduces the computational burden during real-time processing, thereby reducing processing time while maintaining visual quality.
Data Source
AI summary
According to the disclosure of the present document, it is possible for various LMCS application cases to apply an LMCS procedure to a block having a dual tree structure. In addition, the coding performance of the block can be improved. According to the disclosure of the present document, resources required for the LMCS procedure can be reduced. Therefore, the complexity of the LMCS can be reduced and the video/image coding efficiency can be increased.