LMCS Image Coding Chroma Residual Scaling via Bit Shifting
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Solution Overview
Problem
Current image/video compression technologies face inefficiencies in compressing and transmitting high-resolution, high-quality image/video data, particularly in reducing the complexity of the reshaping and scaling process in luma mapping chroma scaling (LMCS) based image coding, which increases transmission and storage costs.
Innovation Solution
The method determines whether reshaping is performed for luma prediction sample values based on whether the current block belongs to a reshaped domain or its prediction mode, allowing for efficient chroma residual scaling by deriving a chroma residual scaling index through simple bit shifting operations and applying reshaping to the average luma value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reshaping is applied to each luma sample value for chroma residual scaling, then chroma scaling accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent divides the luma sample values into multiple bins based on their magnitude ranges. Instead of processing each individual luma sample value through complex reshaping functions, the method segments them into discrete bins and applies simplified scaling operations within each bin, thereby reducing computational complexity while maintaining acceptable chroma scaling accuracy.
Solution Approach 2:
The patent transforms the continuous luma sample values into discrete bin indices through parameter quantization. By changing the parameter representation from continuous amplitude values to discrete bin indices, the complex reshaping operations are replaced with simpler index-based scaling operations, reducing computational burden while preserving essential chroma scaling functionality.
2Measurement precision
If high-resolution, high-quality image/video data is transmitted, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent applies chroma residual scaling selectively based on local luma characteristics. By analyzing local luma sample values and applying chroma scaling only in regions where it provides significant improvement, the method maintains high image quality in critical areas while avoiding unnecessary processing and data transmission in other regions, thus reducing overall data volume.
Solution Approach 2:
The patent implements partial chroma residual scaling by applying the scaling operation only to specific chroma blocks where the luma-chroma correlation is strong. This partial action approach maintains high image quality where needed while avoiding redundant processing and transmission of data where scaling would provide minimal benefit, effectively reducing transmission and storage costs.
3Productivity
If LMCS processing is applied to improve coding efficiency, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary bin classification of luma sample values before chroma residual scaling. By pre-organizing luma values into bins and pre-calculating bin-based scaling factors, the method prepares necessary data structures in advance, allowing the actual chroma scaling operation to proceed more quickly with reduced real-time processing requirements.
Solution Approach 2:
The patent replaces complex mathematical reshaping functions with simplified lookup table-based operations. By substituting the mechanical computation of continuous reshaping functions with discrete table lookups and simple arithmetic operations, the method maintains compression efficiency while significantly reducing processing time and computational resource requirements.
Data Source
AI summary
According to a method, forward reshaping may be performed for inter prediction luma blocks averaged in a domain reshaped for luma mapping, and inverse reshaping may be performed for intra prediction luma blocks averaged in an original domain or an average luma value of the intra prediction luma blocks inversely mapped in the original domain may be derived. In addition, a chroma residual scaling index may be derived on the basis of a simple bit shifting operation so that the method may perform reshaping for an average luma value and may reduce the number of operations required for the reshaping.