Multi-Hypothesis Chroma Prediction for Lower Bit Rate Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in achieving optimal compression efficiency while maintaining video quality, particularly in the intra prediction mode for chroma blocks, due to limitations in current prediction methods.
Innovation Solution
Implementing a multi-hypothesis-based chroma prediction (MCP) that combines non-linear and linear models, including cross-component linear model (CCLM) and multi-model linear model (MMLM), to enhance prediction accuracy and compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single prediction model (LM mode) is used for chroma block prediction, then the device complexity is reduced, but the coding efficiency is insufficient
Solution Approach 1:
The patent combines multiple prediction models (non-LM mode and LM mode including CCLM and MMLM) into a unified multi-hypothesis-based chroma prediction framework. The decoder obtains and combines different prediction modes to generate final chroma predictions, achieving higher coding efficiency by leveraging the strengths of multiple models rather than relying on a single model.
Solution Approach 2:
The patent implements dynamic selection and combination of different prediction models based on the specific characteristics of each chroma block. The system adapts which prediction modes to use and how to combine them, allowing the prediction mechanism to dynamically adjust to different video content and block characteristics, thereby optimizing coding efficiency without requiring always-complex models.
2Productivity
If multiple prediction models are combined for multi-hypothesis-based chroma prediction, then the coding efficiency is improved, but the device complexity increases
Solution Approach 1:
The patent segments the prediction process into distinct components: non-LM mode prediction and LM mode prediction (which includes CCLM and MMLM). Each segment handles specific aspects of chroma block prediction, and the results are combined to produce the final prediction. This segmentation allows the system to manage complexity by breaking down the overall prediction task into manageable parts while maintaining high coding efficiency.
3Loss of energy
If traditional prediction models are used, then the device complexity is low, but the bit rate is higher and video quality is degraded
Solution Approach 1:
The patent changes the parameters and approaches of prediction models by introducing and combining multiple hypothesis-based prediction modes. Instead of using a single fixed prediction approach, the system varies the prediction parameters and models adapted to the specific chroma block characteristics, enabling better compression (lower bit rate) while maintaining video quality through more accurate predictions.
Data Source
AI summary
Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video coding. In one method, a decoder obtains, for a current chroma block, a non-linear model (non-LM) mode and a linear model (LM) mode, and the LM mode includes a cross component linear model (CCLM) mode and a multi-model linear model (MMLM) mode. The decoder then combines the non-LM mode and the LM mode for a multi-hypothesis-based chroma prediction (MCP) for the current chroma block.