Picture Quality Rate Control for Low-Latency Streaming
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Solution Overview
Problem
Traditional rate control methods in low latency streaming applications often result in excessive bit usage for static scenes and scenes with little motion, leading to inefficient encoding and false detection of scene changes, which can cause unnecessary I-frame encoding.
Innovation Solution
Implementing a picture quality oriented rate control method that selectively adjusts the quantization parameter (QP) for sections of a frame based on motion detection, using metrics like SATD variation and section variance to reduce bit usage while maintaining quality, by refining QP values to limit bit allocation for static or low-motion scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional rate control methods are used, then encoding is performed uniformly across all frame sections, but this results in excessive bit usage for static scenes and false detection of scene changes
Solution Approach 1:
The patent applies local quality by differentiating encoding treatment between static and motion-active regions within the same frame. The encoder divides the frame into multiple sections and applies different quantization parameters (QP) to each section based on detected motion activity. Static sections use higher QP values for aggressive compression, while motion-active sections use lower QP values to preserve quality, thereby reducing overall bit usage without compromising scene change detection accuracy.
Solution Approach 2:
The patent segments the video frame into multiple independent encoding sections that can be processed differently. By dividing the frame into sections and evaluating motion activity independently for each section, the system can apply selective rate control strategies. This segmentation allows the encoder to identify false scene changes in static regions while maintaining proper encoding for genuine motion events.
2Productivity
If uniform quantization parameter is applied to all sections, then encoding simplicity is maintained, but bit allocation efficiency decreases for static or low-motion scenes
Solution Approach 1:
The patent implements dynamic rate control by adjusting quantization parameters in real-time based on motion detection results for each frame section. Rather than using a fixed QP value, the system dynamically modifies QP values according to the motion activity level in each section, allowing optimal bit allocation that adapts to changing scene characteristics and maximizes encoding efficiency.
Solution Approach 2:
The patent changes the quantization parameter values based on motion activity detection. Static sections are assigned higher QP values (e.g., QP+2 to QP+4) to reduce bit usage, while motion-active sections retain lower QP values for better quality. This parameter adjustment is performed selectively across different frame sections, transforming the encoding process from uniform to adaptive and significantly improving bit allocation efficiency.
Data Source
AI summary
A derived quantization parameter for a section of a currently encoding picture of a plurality of pictures is incremented to produce an updated quantization parameter when the derived quantization parameter is less than a minimum quantization parameter for the currently encoding picture. The section is then encoded using the updated quantization parameter. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.