Video Quality Estimation Model for Bit Rate and Frame Rate Tradeoffs
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Solution Overview
Problem
Current video quality estimation methods for audiovisual communication services fail to provide specific and useful guidelines for quality design and management, particularly in balancing coding bit rate and frame rate to achieve optimal video quality, as they do not adequately consider the tradeoff between these parameters.
Innovation Solution
A video quality estimation apparatus and method that extracts key parameters such as coding bit rate and frame rate, specifies an estimation model representing the relationship between these parameters and subjective video quality, and outputs an estimation value of the quality a viewer senses, allowing for informed quality design and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the coding bit rate is increased to improve spatial video quality, then the frame rate decreases due to bandwidth constraints, resulting in temporal quality degradation
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting both coding bit rate and frame rate based on network conditions and content characteristics. The system modifies these parameters to find optimal combinations that balance spatial and temporal quality, rather than fixing one parameter while the other deteriorates.
Solution Approach 2:
The invention implements dynamics by creating a quality evaluation model that continuously adapts to changing network conditions and traffic types. The system dynamically determines optimal coding parameters and frame rates based on real-time conditions, making the quality optimization process flexible and responsive rather than static.
2Speed
If the frame rate is increased to improve temporal video quality, then the coding bit rate must be reduced, leading to spatial quality degradation
Solution Approach 1:
The system changes parameters by simultaneously considering both frame rate and coding bit rate in the quality evaluation model. It determines optimal values for both parameters based on network conditions and content characteristics, ensuring that increasing frame rate does not unnecessarily sacrifice spatial quality when bit rate allows.
Solution Approach 2:
The invention applies dynamics by making the quality evaluation adaptive to different traffic types and network conditions. The system dynamically adjusts the balance between frame rate and coding bit rate based on content characteristics, enabling flexible optimization that responds to changing requirements rather than following a fixed tradeoff.
3Device complexity
If conventional video quality estimation methods are used, then the evaluation process becomes complex and fails to provide specific guidelines for quality design, but simpler methods lack accuracy in expressing viewer-perceived quality
Solution Approach 1:
The patent extracts the essential factors affecting video quality (coding bit rate, frame rate, packet loss rate) from the complex encoding and transmission process. By focusing on these key parameters and their relationships, the system simplifies the quality evaluation while maintaining accuracy in predicting viewer-perceived quality.
Solution Approach 2:
The invention applies feedback by using the quality evaluation results to guide quality design and parameter optimization. The system provides specific guidelines for quality design based on the evaluation model, creating a closed-loop process where quality assessment informs parameter selection and system configuration.
Data Source
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AI summary
In estimating subjective video quality corresponding to main parameters (121/221) which are input as an input coding bit rate (121B/221B) representing the number of coding bit rates per unit time and an input frame rate (121A/221A) representing the number of frames per unit time of an audiovisual medium, an estimation model specifying unit specifies, on the basis of the input coding bit rate (121B/input frame rate (221A)), an estimation model (122/222) representing the relationship between subjective video quality and the frame rate (/coding bit rate) of the audiovisual medium. Subjective video quality corresponding to the input frame rate (121A/input coding bit rate 221B) is estimated by using the specified estimation model (122/222) and output as an estimation value (123/223).