Image Coding Unit QP Control for Bit Rate and Reconstruction Quality
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Solution Overview
Problem
Existing image encoding and decoding systems face issues with poor quality of reconstructed images due to inaccurate quantization parameter (QP) determination, which is based on empirical data and does not consider image content, leading to inefficient bit rate control.
Innovation Solution
The proposed method determines the quantization parameter (QP) by considering the image content, number of lossy bits, and bitstream buffer fullness to dynamically set a target number of bits for each coding unit, ensuring accurate bit rate control and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a larger QP is used for encoding, then the number of coded bits is reduced, but the quality of the reconstructed image deteriorates
Solution Approach 1:
The patent implements dynamic QP adjustment by dividing the image into multiple regions and assigning different QP values to each region based on its characteristics. The rate control module dynamically selects QP values from different fullness ranges (first, second, or third range) depending on the buffer fullness state and region importance, rather than using a fixed or uniformly clipped QP value for the entire image.
Solution Approach 2:
The patent applies different QP values to different regions of the image based on their importance and complexity. Important regions (e.g., foreground objects) receive smaller QP values for higher quality, while less important regions (e.g., background) receive larger QP values for better compression. This local differentiation resolves the contradiction by allowing quality optimization where needed while maintaining overall bit rate efficiency.
2Manufacturing precision
If a smaller QP is used for encoding, then the quality of the reconstructed image is improved, but the number of coded bits increases
Solution Approach 1:
The rate control module dynamically adjusts QP values based on buffer fullness state. When the buffer has sufficient space, smaller QP values can be used to improve quality without causing buffer overflow. When the buffer is nearly full, the system switches to larger QP values to reduce bit rate and prevent overflow, thus managing the quality-bit rate trade-off dynamically rather than statically.
Solution Approach 2:
The patent applies smaller QP values selectively to important regions where quality is prioritized, while using larger QP values in less important regions to control the overall bit rate. This localized approach allows the system to improve perceived image quality in critical areas without proportionally increasing the total number of coded bits.
3Ease of operation
If empirical data-based fullness ranges are used for QP clipping, then the rate control process is simplified, but the accuracy of QP determination deteriorates
Solution Approach 1:
The rate control module uses feedback from the buffer fullness state to dynamically adjust QP values. The system continuously monitors the buffer status and adjusts the QP selection strategy accordingly, switching between different fullness ranges based on real-time conditions. This feedback mechanism improves QP determination accuracy without significantly complicating the rate control process.
Solution Approach 2:
The patent changes the QP parameter dynamically based on buffer fullness conditions and region characteristics. Instead of using fixed empirical thresholds, the system adjusts QP values according to multiple parameters including buffer state, region importance, and image complexity, thereby improving determination accuracy while maintaining operational feasibility through structured decision logic.
Data Source
AI summary
When a to-be-decoded bitstream of a coding unit in an image bitstream is decoded, or a to-be-encoded coding unit in a current frame is encoded, three factors are considered: image content of the coding unit, a number of lossy bits, and a buffer fullness of a bitstream buffer, and a target number of bits is dynamically set. The decoder decodes the bitstream of the coding unit based on the quantization parameter determined based on the target number of bits.