Intra Prediction Mode Weighting for Better Video Compression
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Solution Overview
Problem
Existing video coding standards like H.264/AVC and H.265/VVC fail to efficiently handle the intra prediction process due to the intra prediction mode decision, leading to suboptimal compression efficiency.
Innovation Solution
An intra prediction method that determines a prediction mode parameter, selects at least two prediction modes, calculates a first and second cost for each mode, and combines them using a weight combination to improve accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional intra prediction mode decision is used, then device complexity is reduced, but compression efficiency deteriorates
Solution Approach 1:
The prediction process is segmented into multiple stages: template matching stage, candidate mode selection stage, and final prediction stage. This segmentation allows complex operations to be performed only where needed (template-based regions) while using simpler methods elsewhere, improving compression efficiency without uniformly increasing complexity across the entire prediction process.
Solution Approach 2:
Different prediction strategies are applied to different regions within the current block based on template matching results. Regions with high template similarity use derived prediction modes, while other regions use traditional candidate modes. This local differentiation optimizes compression efficiency for specific regions without unnecessarily complicating the entire prediction process.
2Measurement precision
If multiple prediction modes are evaluated, then intra prediction accuracy is improved, but computational cost increases
Solution Approach 1:
Template matching is performed as a preliminary action before selecting candidate prediction modes. This preliminary step identifies regions where multiple mode evaluation would be beneficial, allowing the system to focus computational resources on areas where they will most improve prediction accuracy, rather than uniformly evaluating multiple modes across the entire block.
Solution Approach 2:
The method dynamically changes the set of prediction modes evaluated based on template matching results. When template similarity exceeds a threshold, the system switches from evaluating a fixed set of candidate modes to evaluating derived modes based on template characteristics. This parameter change adapts the computational effort to the actual content requirements, improving accuracy when needed while reducing computational cost when templates provide sufficient information.
Data Source
AI summary
An intra prediction method and a decoder are provided. The method includes the following. A prediction mode parameter is obtained, where the prediction mode parameter indicates that an intra prediction value is to be determined in a derivation manner. At least two prediction modes are determined according to the derivation manner. A first weight combination related to the at least two prediction modes is determined. A first cost for performing prediction on a template region of a current block in the at least two prediction modes is determined according to the at least two prediction modes and the first weight combination. A second cost for performing prediction on the template region in a first prediction mode is determined according to the first prediction mode. An intra prediction value of the current block is determined according to the first cost and the second cost.