Video Quality Estimation via Packet Loss Degradation Model
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Solution Overview
Problem
Current video quality estimation methods for audiovisual communication services fail to provide specific guidelines for quality design and management, particularly in considering the influence of packet loss rate on video quality, which varies with coding bit rate and frame rate.
Innovation Solution
A video quality estimation apparatus and method that extracts key parameters such as coding bit rate, frame rate, and packet loss rate, using a degradation model to correct subjective video quality estimates, thereby providing actionable guidelines for quality management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional video quality estimation methods are used, then quality design and management guidelines cannot be provided, but the patent enables accurate quality estimation by considering packet loss rate influence
Solution Approach 1:
The quality estimation process is segmented into distinct functional modules: parameter extraction unit for obtaining coding bit rate, frame rate, and packet loss rate; degradation model specifying unit for determining quality degradation based on packet loss; and video quality correction unit for adjusting reference quality values. This segmentation allows each module to handle specific aspects independently, improving accuracy while maintaining manageable system complexity.
Solution Approach 2:
The system performs preliminary extraction of key parameters (coding bit rate, frame rate, packet loss rate) before conducting the actual quality estimation. The degradation model is specified in advance based on these parameters, and reference subjective video quality is pre-determined without packet loss. This preliminary action enables the correction process to focus solely on adjusting for packet loss effects, improving efficiency and accuracy.
2Measurement precision
If multiple parameters (coding bit rate, frame rate, packet loss rate) are considered, then accurate quality estimation is achieved, but the complexity of quality management increases
Solution Approach 1:
The degradation model specifying unit acts as an intermediary that processes multiple input parameters (coding bit rate, frame rate, packet loss rate) and translates them into a corrected video quality value. This intermediary component consolidates the complexity of handling multiple parameters, presenting a simplified interface for quality management while maintaining accurate estimation based on all relevant factors.
Solution Approach 2:
The system dynamically adjusts the video quality estimation based on changes in key parameters. When packet loss rate, coding bit rate, or frame rate changes, the degradation model is re-specified to reflect new conditions, and the reference quality is corrected accordingly. This parameter-driven approach enables accurate quality estimation across varying conditions while maintaining operational simplicity through automated adjustments.
Data Source
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AI summary
In estimating subjective video quality corresponding to main parameters (21) which are input as an input frame rate (21A) representing the number of frames per unit time, an input coding bit rate (21B) representing the number of coding bits per unit time, and an input packet loss rate (21C) representing a packet loss occurrence probability of an audiovisual medium, a degradation model specifying unit (12) specifies a degradation model (22) representing the relationship between the packet loss rate and the degradation in reference subjective video quality (23) on the basis of the input frame rate (21A) and input coding bit rate (21B). A desired subjective video quality estimation value (24) is calculated by correcting the reference subjective video quality on the basis of a video quality degradation ratio corresponding to the input packet loss rate (21C) calculated by using the degradation model (22).