Non-Intrusive Video Quality Assessment via Packet Parameter Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current non-intrusive video quality assessment systems for packet switched telecommunications networks are limited in measuring video compression degradation, as they primarily focus on network conditions and lack parameters to account for temporal and spatial characteristics of video frames encoded in packets.
Innovation Solution
A method and apparatus that estimate video quality by extracting parameters from packet sequences, including frame rate and encoded data size, to generate an estimated Mean Opinion Score (MOS) for each frame group, using timestamps and payload sums to assess video quality in real-time without disrupting live traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If non-intrusive quality assessment systems focus on network conditions, then implementation simplicity is improved, but measurement precision of video compression degradation worsens
Solution Approach 1:
The system segments the quality assessment into multiple independent parameter extractions: temporal characteristics (frame rate, inter-frame redundancy) and spatial characteristics (frame size, block distortion metrics). Each parameter is extracted separately from packet sequences and then combined to form a comprehensive quality assessment, allowing modular implementation while achieving precise measurement of compression degradation.
Solution Approach 2:
The system changes from traditional single-parameter assessment to multi-parameter assessment by introducing frame rate, frame size, inter-frame redundancy, and block distortion metrics. These parameter changes enable the system to capture both temporal and spatial characteristics of video compression, significantly improving measurement precision without requiring complex intrusive testing.
2Ease of operation
If traditional quality assessment methods are used, then ease of operation is improved, but adaptability to temporal and spatial video characteristics worsens
Solution Approach 1:
The system creates a universal quality assessment framework that can evaluate multiple video characteristics simultaneously. By extracting both temporal parameters (frame rate, inter-frame redundancy) and spatial parameters (frame size, block distortion) from the same packet sequence, the system achieves multi-functionality without requiring separate testing procedures, maintaining ease of operation while enhancing adaptability.
Solution Approach 2:
The system adds temporal and spatial dimensions to traditional quality assessment by incorporating frame rate (temporal dimension) and frame size/block metrics (spatial dimension) alongside traditional network condition parameters. This dimensional expansion allows the system to adapt to diverse video characteristics while maintaining a unified assessment approach that is easy to operate.
Data Source
AI summary
This invention relates to a non-intrusive video quality assessment system. A method and apparatus are provided in which video frame parameters are extracted from a sequence of packets by generating a first video quality parameter for each group of packets associated with a particular frame of video data in dependence upon the frame rate of the video stream; and generating a second video quality parameter for each of said group of packets in dependence upon the size of encoded data comprising the video frame.