Luma Mapping With Chroma Scaling for Lower-Complexity Video Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution, high-quality image/video data, particularly in immersive media formats like VR and AR, necessitates a highly efficient compression technology to reduce transmission and storage costs while maintaining subjective/objective visual quality.
Innovation Solution
Implementing luma mapping with chroma scaling (LMCS) processes that include efficient filtering, constrained codewords, linear mapping, and flexible bin usage, along with simplified inverse mapping index derivation to enhance image/video coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution, high-quality image/video data is transmitted or stored using existing broadband lines or storage media, then image quality is maintained, but transmission cost and storage cost increase
Solution Approach 1:
The patent applies luma mapping with chroma scaling (LMCS) to transform the parameter representation of image/video data. By mapping luma values to a reduced set of codewords and scaling chroma residuals, the patent changes how visual information is encoded, achieving high compression ratios while preserving perceived image quality
Solution Approach 2:
The patent applies different processing strategies to different components of the image data: luma components undergo mapping to discrete codewords while chroma components undergo residual scaling. This local differentiation optimizes compression for each component based on its visual importance and characteristics
2Productivity
If luma mapping with chroma scaling (LMCS) process is performed to improve compression efficiency and visual quality, then compression efficiency and visual quality increase, but computational complexity increases
Solution Approach 1:
The patent segments the LMCS process into distinct stages: luma mapping to codewords, chroma residual calculation, and chroma scaling. This segmentation allows each stage to be optimized independently and enables selective application based on content characteristics
Solution Approach 2:
The patent allows for selective application of full LMCS processing versus simplified versions. In some cases, only luma mapping is applied, or chroma scaling is omitted, providing a trade-off between compression efficiency and computational complexity based on specific content requirements
Data Source
AI summary
According to the disclosure of the present document, a luma mapping with chroma scaling (LMCS) process may be simplified, and a linear LMCS may be applied. Accordingly, the complexity of the LMCS may be reduced and video/image coding efficiency may be increased.