Chroma From Luma Prediction Mapping for High-Resolution Video Coding
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in chroma prediction, particularly in high-resolution video streams, leading to increased bandwidth and storage requirements due to the lack of effective methods for chroma from luma prediction.
Innovation Solution
Implementing chroma from luma (CfL) prediction methods that map luma samples to neighbor chroma samples for improved prediction, utilizing various types of CfL prediction processes to enhance coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional chroma prediction methods are used, then video coding can be performed with basic compression, but bandwidth and storage requirements increase significantly for high-resolution video streams
Solution Approach 1:
The patent changes the prediction parameters by introducing multiple CfL prediction types (first CfL prediction and second CfL prediction) with different mapping approaches between luma and chroma samples. This allows the system to adapt the prediction parameters based on block characteristics, achieving better compression efficiency while reducing the quantity of chroma data that needs to be stored and transmitted.
Solution Approach 2:
The patent implements dynamic selection between different CfL prediction types based on the properties of the current video block. The system dynamically switches between first CfL prediction (using a first mapping) and second CfL prediction (using a second mapping) to optimize performance for different block types, thereby improving coding efficiency without uniformly increasing bandwidth requirements.
2Quantity of substance
If chroma sub sampling is applied to reduce bandwidth, then storage requirements decrease, but prediction accuracy and coding efficiency deteriorate
Solution Approach 1:
The patent introduces luma samples as an intermediary to predict chroma samples. Instead of directly storing and transmitting full chroma data, the system uses luma samples (which are already present in the decoded image) as a mediator to generate predicted chroma values through CfL prediction. This intermediary approach allows for accurate chroma prediction with reduced storage requirements.
Solution Approach 2:
The patent creates copies of chroma prediction data by deriving chroma sample values from luma sample values through the CfL prediction process. Rather than storing original chroma data, the system generates predicted chroma copies based on luma information, reducing the actual storage needed while maintaining prediction accuracy for the chroma components.
3Productivity
If multiple CfL prediction types are implemented, then coding efficiency improves, but device complexity increases
Solution Approach 1:
The patent segments the chroma prediction process into distinct types (first CfL prediction and second CfL prediction), each with its own specific mapping rules and application conditions. By dividing the complex prediction task into manageable segments, the system can implement multiple prediction types while maintaining clear, organized complexity that is easier to manage and process.
Data Source
AI summary
This disclosure relates to video processing that includes: determining that a chroma block is to be predicted in a Chroma from Luma (CfL) mode, wherein the chroma block corresponds to a luma block; mapping a plurality of luma samples of the luma block to a plurality of neighbor chroma samples in at least one neighbor chroma block that neighbors the chroma block; and performing a CfL prediction of the chroma block using the plurality of neighbor chroma samples as a plurality of prediction samples of the chroma block. This disclosure also relates to video processing that includes: determining a type of chroma from luma (CfL) prediction process from among a plurality of different types of CfL prediction processes; and performing a CfL prediction process according to the type of CfL prediction process.