“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!