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“POLITEHNICA” UNIVERSITY OF TIMIȘOARAFACULTY OF ELECTRONICS AND
TELECOMMUNICATIONSDEPARTMENT OF COMMUNICATIONS
DIPLOMA THESIS
VIDEO QUALITY ASSESSMENT IN MOBILE NETWORKS
Coordinate,Assoc. Prof. Eng. Dr. Eugen Mârza
Graduate,Dragoș-Florin Iancu
Timișoara 2010
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Contents
1) Introduction
2) Human Visual System (HVS)3) Mobile Video Streaming Principles
4) Quality Metrics
5) Conclusions
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Introduction
Topics of interest:• vision modeling in the framework of video quality
assessment• analysis and evaluation of different video quality
assessment methods and algorithms over a mobile network
• determining the one that performs best while
correlating well with subjective assessments• error detection and concealment (artifacts)
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Human Visual System
• HVS:– very complex– highly adaptive– not equally sensitive to all stimuli – visual information processed on different pathways and channels– color perception based on different spectral
sensitivities of photoreceptors
=> characteristics of the HVS used in the design of vision models and quality metrics
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Mobile Video Streaming Principles
• Video service request in a mobile network– wireless=error prone environment – limited bandwidth means low resolution => loss of 1
packet is a considerable loss of information– real-time => retransmission impossible
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Subjective & Objective Quality Assessment
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Distortion Artifacts
• Blocking artifacts • Ringing artifacts• Clipping• Noise • Contrast• Sharpness• Blurriness • Jerkiness• Mosquito Noise• Shimmering• Network errors • Post-processing errors
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Quality Metrics
a) MOS (Mean Opinion Score)
Subjective test
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Quality Metrics
b) PSNR (Peak Signal to Noise Ratio)
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Quality Metrics
c) SSIM (Structural Similarity)
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Quality Metrics
• SSIM simple and multiscale plugins in ImageJ
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Conclusions
1. Best results with PSNR metric2. SSIM best mimics the HVS, however has
limitations 3. MOS delivers valuable information for:
– optimization – benchmarking
4. methods dependent on: – the correct receival of motion vectors– the presence of scene cuts or fast movement
5. systematic video quality assessment approaches developed to increase flexibility
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Thank You!
