Adaptive Quantization Matrix Selection for Video Image Quality
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional quantization matrix encoding/decoding methods fail to consider factors such as prediction mode, color component, size, form, one-dimensional transform type, and two-dimensional transform combination, limiting the objective and subjective image quality of high-resolution and high-quality images.
Innovation Solution
A method and apparatus that determine adaptation parameter sets including quantization matrices, considering prediction mode, color component, size, and transform type, to improve image quality by dequantizing and reconstructing blocks based on these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional quantization matrix encoding/decoding is used considering only prediction mode, color component, and size, then the encoding process is simple, but the objective and subjective image quality is limited
Solution Approach 1:
The patent extends the quantization matrix selection parameters from conventional three factors (prediction mode, color component, size) to seven factors by adding form, one-dimensional transform type, and two-dimensional transform combination. This parameter expansion enables more precise image quality optimization while maintaining a systematic encoding approach that manages the increased complexity through structured parameter grouping and adaptive selection mechanisms
2Manufacturing precision
If multiple quantization matrices are selected based on prediction mode, color component, size, form, and transform types, then image quality is improved, but the complexity of determining and managing adaptation parameter sets increases
Solution Approach 1:
The patent segments the quantization matrix selection process into distinct adaptation parameter sets, each configured for specific combinations of prediction mode, color component, size, form, and transform types. This segmentation allows the encoder to manage complexity by organizing multiple quantization matrices into structured groups that can be selectively applied based on the current block's characteristics, rather than managing all parameters in a single undifferentiated system
Solution Approach 2:
The patent implements dynamic adaptation parameter set selection where the encoder determines which adaptation parameter set to use based on the actual characteristics of each current block. This dynamic approach allows the system to adaptively choose the most appropriate quantization matrix configuration for each block, optimizing image quality while managing complexity through context-dependent parameter selection rather than static universal application
Data Source
AI summary
Disclosed herein is a video decoding method including determining one or more adaptation parameter sets including a quantization matrix set including a plurality of quantization matrices, determining an adaptation parameter set including a quantization matrix set applied to a current picture or a current slice from among the one or more adaptation parameter sets, dequantizing transform coefficients of a current block of a current picture or a current slice based on the quantization matrix set of the determined adaptation parameter set, and reconstructing the current block based on the dequantized transform coefficients, wherein the adaptation parameter set includes coding information applied to one or more pictures or slices.