Image Encoding With Adaptive Chroma Quantization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image encoding methods, such as HEVC and VVC, face inefficiencies in encoding artificial images due to unnecessary increases in code amount when using quantization parameters less than 4, leading to suboptimal image quality and increased data size.
Innovation Solution
Adaptive correction of quantization parameters by determining whether to perform transform processing on chroma components, using a reference value as a quantization parameter when transform processing is not performed, to reduce unnecessary code increase and improve encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If quantization parameter is set smaller than 4 to increase gradations, then image quality after compression is improved, but amount of code increases unnecessarily
Solution Approach 1:
The patent dynamically adjusts the quantization parameter based on the transform processing status. When transform processing is skipped, the quantization parameter is corrected to a reference value (typically 4) instead of using the originally small value, thereby preventing unnecessary code increase while maintaining acceptable image quality through adaptive parameter modification
Solution Approach 2:
The encoding device determines whether transform processing is performed on chroma components and uses this information to feedback-adjust the quantization parameter. This closed-loop control ensures that the quantization parameter is appropriately modified based on the actual processing path taken, preventing code increase when transform is skipped
2Productivity
If transform processing is skipped on chroma component, then encoding efficiency is improved, but image quality does not improve and code amount increases
Solution Approach 1:
When transform processing is skipped, the patent applies parameter change by correcting the quantization parameter to a reference value. This ensures that even without transform processing, the quantization step remains appropriate (typically 1 when QP=4), maintaining image quality while preserving the encoding efficiency benefits of skipping transform
3Manufacturing precision
If quantization parameter is set smaller than 4, then gradations are increased, but encoding efficiency deteriorates due to greater code amount
Solution Approach 1:
The patent implements adaptive parameter changes by modifying the quantization parameter based on transform processing status. When transform is skipped, the quantization parameter is corrected to prevent excessive gradation increase, thereby maintaining encoding efficiency while preserving necessary image quality through intelligent parameter adjustment
Data Source
AI summary
The block to be encoded is encoded using a first quantization parameter corresponding to a coefficient of each color component in the block to be encoded when it is determined that orthogonal transform processing is to be performed on the coefficient of each color component in the block to be encoded, and the block to be encoded is encoded using a second quantization parameter obtained by correcting the first quantization parameter when it is determined that orthogonal transform processing is not to be performed on the coefficient of each color component in the block to be encoded. A predetermined determination based on the first quantization parameter and a predetermined value is performed, and the second quantization parameter is derived by correcting the first quantization parameter in accordance with a determination result of the predetermined determination.