Image Decoding Device Weighted Averaging for Geometric Partitioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing geometric partitioning mode (GPM) techniques for image decoding have limited weighted averaging patterns, resulting in suboptimal encoding performance.
Innovation Solution
An image decoding device and method that employs a circuit or program to decode control information and quantized values, performing inverse quantization and transform, generating predicted samples through weighted averaging using variable weighting coefficients based on the decoded control information to improve encoding efficiency in GPM.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If limited weighted averaging patterns are used in GPM, then device complexity is reduced, but encoding performance deteriorates
Solution Approach 1:
The patent applies dynamics by making the weighting coefficients variable rather than fixed. The weighting coefficients are determined based on the distance from the division boundary, allowing the blending operation to adapt dynamically to different boundary positions and characteristics. This resolves the contradiction by providing flexible, context-appropriate weighting without requiring multiple predefined patterns, thus improving encoding performance while maintaining device complexity at an acceptable level.
Solution Approach 2:
The patent changes the parameter of weighting coefficients from fixed pattern-based values to distance-dependent variable values. By calculating weighting coefficients based on the distance from the division boundary, the system achieves more precise control over the blending operation. This parameter change enables better adaptation to diverse boundary conditions, improving encoding performance without requiring complex predefined patterns.
2Productivity
If more weighted averaging patterns are used to improve encoding performance, then encoding performance improves, but device complexity increases
Solution Approach 1:
Instead of increasing the number of predefined patterns, the patent changes the parameter determination method from pattern selection to distance-based calculation. This allows the system to achieve high encoding performance through continuous, context-appropriate weighting coefficients rather than discrete pattern choices, avoiding the complexity increase that would result from supporting multiple patterns.
Solution Approach 2:
The system performs self-service by automatically determining appropriate weighting coefficients based on the geometric properties of the division boundary itself. Rather than requiring external pattern selection or complex control logic, the boundary's own characteristics (distance from samples to boundary) directly determine the weighting, simplifying the overall system while improving performance.
Data Source
AI summary
In an image decoding device according to the present invention, a circuit: decodes control information and a quantized value; obtains a decoded transform coefficient by performing inverse quantization on the decoded quantized value; obtains a decoded prediction residual by performing inverse transform on the decoded transform coefficient; generates a first predicted sample based on a decoded sample and the decoded control information; accumulates the decoded sample; generates a second predicted sample based on the accumulated decoded sample and the decoded control information; generates a third predicted sample by weighted averaging using one of weighting coefficients limited based on the decoded control information for at least one of the first predicted sample or the second predicted sample; and obtains the decoded sample by adding the decoded prediction residual and the third predicted sample.