Template Matching Cost Signaling for Nonlinear Video Prediction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently utilizing template matching for intra and inter predictions, leading to suboptimal compression efficiency.
Innovation Solution
Implement a non-linear function-based prediction method using template matching, where a prediction model is determined based on template matching costs between a current block and a reference block, applying a non-linear function to process samples and determine a prediction block.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching prediction is used for video coding, then prediction accuracy is improved, but compression efficiency is suboptimal
Solution Approach 1:
The patent applies non-linear function transformations to the template matching prediction process, changing the parameters of the prediction model from simple linear combinations to non-linear functions that can capture more complex relationships between template blocks and current blocks, thereby improving compression efficiency while maintaining prediction accuracy
Solution Approach 2:
The patent introduces dynamic selection of prediction models based on template matching costs, where the system adapts which prediction model to use (linear, non-linear, or none) depending on the specific characteristics of the current block and reference block, optimizing compression efficiency for each case
2Measurement precision
If multiple candidate prediction models are evaluated, then prediction quality is improved, but processing complexity increases
Solution Approach 1:
The patent uses template matching costs as feedback to guide the selection of prediction models, where the cost calculation provides information about which models perform best for each specific case, allowing the system to efficiently select the optimal model without exhaustively evaluating all possibilities
Solution Approach 2:
The patent evaluates multiple candidate prediction models but only to the extent necessary to determine the optimal one, using template matching costs to prune the search space and avoid unnecessary computation, achieving good prediction quality without excessive processing complexity
Data Source
AI summary
An apparatus including processing circuitry is provided. The processing circuitry is configured to, when a first syntax element indicates that a non-linear function-based prediction method is applied to reconstruct a current block, determine a prediction model from a plurality of candidate prediction models based on a plurality of TM costs between a template of the current block and a template of a reference block according to the plurality of candidate prediction models associated with the non-linear function-based prediction method. The processing circuitry is configured to determine a prediction block of the current block as the reference block processed by a non-linear function of the prediction model.