Video Encoder Quantization Rounding Offset Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video encoding technologies face challenges in preserving fine details, especially in smooth regions, due to constant rounding offset assumptions, which affect perceptual quality and bit rate regulation.
Innovation Solution
Jointly adjusting quantization step size and rounding offset based on block characteristics, such as smoothness and texture, to optimize bit allocation and preserve fine details in smooth areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the quantization rounding offset is kept constant and only the quantization step size is adjusted, then the device complexity is reduced and ease of operation is improved, but the manufacturing precision of fine details in smooth regions deteriorates
Solution Approach 1:
The patent applies the Dynamics principle by making the rounding offset adjustable and adaptive rather than fixed. The rounding offset is dynamically modified based on local picture characteristics (smoothness measures) to preserve fine details in smooth regions while maintaining operational flexibility. This allows the system to adapt the quantization process to different regions of the image, improving manufacturing precision without sacrificing ease of operation.
Solution Approach 2:
The patent implements Local quality by applying different rounding offset values to different regions of the picture based on their smoothness characteristics. Smooth regions receive adjusted rounding offsets to preserve fine details, while other regions use standard values. This localized adaptation ensures that precision improvements are applied where needed without unnecessarily complicating the overall system.
2Manufacturing precision
If the bit rate is increased to preserve fine details in smooth regions, then the manufacturing precision is improved, but the loss of energy increases
Solution Approach 1:
The patent applies Parameter changes by modifying the rounding offset parameter based on local picture characteristics rather than uniformly increasing the bit rate. By changing this specific parameter adaptively across different regions, the system preserves fine details in smooth areas while maintaining energy efficiency overall, avoiding the need to increase bits everywhere.
Solution Approach 2:
The patent uses Local quality by applying enhanced precision (adjusted rounding offsets) only where needed in smooth regions rather than across the entire picture. This selective approach preserves fine details where visible artifacts occur while avoiding unnecessary bit allocation in textured regions, thereby reducing overall energy loss.
3Manufacturing precision
If the quantization step size is reduced to preserve fine details, then the manufacturing precision is improved, but the productivity decreases due to increased bit rate
Solution Approach 1:
The patent implements Local quality by applying fine detail preservation (adjusted rounding offsets) only in smooth regions where it is visually necessary, rather than across the entire picture. This selective approach maintains manufacturing precision where needed while avoiding the productivity penalty of uniformly increasing bit rates across all regions including textured areas.
Solution Approach 2:
The patent appliesParameter changes by modifying the rounding offset parameter locally based on picture characteristics rather than globally reducing the quantization step size. This targeted parameter adjustment preserves fine details in smooth regions without the need to reduce quantization step size everywhere, thereby maintaining productivity.
4Manufacturing precision
If the rounding offset is increased to preserve small coefficients, then the manufacturing precision of fine details is improved, but the loss of information in large coefficients increases
Solution Approach 1:
The patent appliesLocal quality by using different rounding offset values in different regions based on smoothness characteristics. In smooth regions, adjusted rounding offsets preserve small coefficients and fine details. In other regions, standard rounding offsets are used to maintain proper quantization of large coefficients, avoiding information loss through selective regional adaptation.
Solution Approach 2:
The patent implementsParameter changes by adaptively modifying the rounding offset parameter based on local picture characteristics. This allows the system to increase rounding offsets where needed to preserve fine details while maintaining appropriate quantization behavior in other regions, balancing the preservation of small coefficients with the retention of large coefficient information.
Data Source
AI summary
The present principles provides a method and apparatus for jointly adjusting the rounding offset and the quantization step size on a macroblock level to improve the perceptual quality of the fine details of the encoded image. In one implementation, the content of the pictures is analyzed and the smooth regions are identified. A quantization step size value for the picture is initially defined and a rounding offset is adaptively assigned to each macroblock based on the content characteristics. The quantization step size is then calculated for the a particular macroblock according to another content characteristic of the macroblock such that the encoding of the particular macroblock is performed in response to the calculated quantization step size and the rounding offset value of the first block.