Luma Mapping Chroma Scaling Video Coding
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, such as 4K or 8K, poses challenges in efficient compression, transmission, storage, and reproduction due to the high amount of information required, leading to increased costs and resource utilization.
Innovation Solution
The implementation of a method and apparatus for efficient luma mapping with chroma scaling (LMCS) that includes constrained LMCS codewords, a single chroma residual scaling factor, linear mapping, explicit signaling of pivot points, flexible bin numbers for luma mapping, and simplified index derivation procedures for inverse luma mapping and chroma residual scaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution, high-quality image/video (4K or 8K) is transmitted or stored using existing mediums, then image quality is improved, but transmission cost and storage cost increase due to high amount of information
Solution Approach 1:
The patent applies luma mapping with chroma scaling (LMCS) that transforms the parameter representation of image data by mapping luma values to a reduced set of representative values and scaling chroma values based on luma characteristics. This parameter transformation reduces the amount of information needed to represent high-resolution images while maintaining visual quality, directly resolving the contradiction between image quality and information quantity.
2Productivity
If luma mapping with chroma scaling (LMCS) procedure is performed to improve compression efficiency and visual quality, then coding efficiency is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the image processing into distinct stages: luma mapping (transforming luma values to representative values), chroma residual scaling (scaling chroma based on luma characteristics), and selective application to different blocks. This segmentation allows the complex LMCS procedure to be applied efficiently and selectively, reducing overall computational complexity while maintaining compression efficiency benefits.
Solution Approach 2:
The patent enables partial application of LMCS by allowing selective activation of luma mapping and chroma scaling for different blocks or regions based on content characteristics. This partial action approach applies the computationally intensive LMCS procedure only where necessary to achieve compression efficiency gains, rather than uniformly across all image data, thus reducing overall processing requirements.
3Adaptability or versatility
If flexible number of bins is used for luma mapping and simplified index derivation procedure is implemented, then coding flexibility and efficiency are improved, but precision in representing luma values may be reduced
Solution Approach 1:
The patent implements dynamic bin allocation where the number of bins for luma mapping can be adjusted based on content characteristics and coding conditions. This dynamic approach allows the system to use fewer bins (reducing precision) when flexibility and compression are prioritized, or more bins (maintaining precision) when higher accuracy is needed, thus resolving the contradiction between adaptability and precision through conditional parameter adjustment.
Data Source
AI summary
According to the disclosure of the present document, the granularity of value(s) of a chroma residual scaling factor can be controlled through explicit signaling of information on the value(s) of the chroma residual scaling factor. In addition, chroma residual scaling can be efficiently performed through implicit derivation of the information on the value(s) of the chroma residual scaling factor.