The Influence of Packet Loss On Video Quality By: Revital and Merav Huber.

1. Technion- Israel Institute of Technology Faculty of Electrical EngineeringCCIT-Computer Network Laboratory The Influence of Packet Loss On Video Quality By: Revital and Merav Huber. Supervisor: Dr. Ofer Hadar. Winter 1998/9

2. Analog video  Encoder  Transmitter Receiver  Decoder  Analog video Noisy communication network Original movie Received movie Network Simulation

3. Target • Finding the connection between communication network performance and the quality of a compressed video signal. • Destination: determination of the packet loss model which causes the smallest degradation of the received movie.

4. Loss Models of The Network IID Burst

5. Assumption • Bursts of information loss would be less noticed than other error forms. • reasons: • Error in a number of pixels on consequent frames, is noticed by viewer more than a frame loss, because of movie speed. • When bursts occur, following packets are degraded, which belong to the same frame.

6. Theoretical Background • MPEG • Motion Picture Experts Group • Video & audio signals synchronization. • Video transfer by frames. • Frame types are determined by encoding: • Intracoded: encoded by JPEG. • Predictive: use of block- differences between the previous frame and the present frame. • Bidirectional: use of block- differences between the encoded frame & the previous & the next frames.

7. Theoretical Background, MPEG I frame Bframe B frame Pframe B frame B frame Pframe B frame B frame Pframe

8. MPEG Movies Cirinout.mpg cirinout Received.mpg received

9. Theoretical Background- Quality Factors • Delay • Quantization of MPEG encoding • Lossy network • causes: • errors due to broadcast bursts. • Routing errors. • When buffers are finite and there is overflow, it is possible packets loss will occur.

10. Performance Idea • A lossy network simulation, transmitting a video signal. • The video signal is divided into packets. • The receiver’s information is the arriving packets. • Comparison between the transmitted and received signals, by PSNR. • Measuring edge sharpness by MTF. • Measuring power spectrum.

11. Tested Video Signal

12. Quality Measurements

13. MTF Ideal edge Smeared Edge 1. Image 2. Gray Level x x 3. LSF x x 4. MTF 1 1 False response f f

14. Results - Example

15. Results - PSNR Pe=0.02 Burst IID

16. Results - MTF Pe=0.01 Burst IID

17. Results - Power Spectrum Pe=0.02 Burst IID

18. Conclusions • Burst loss model effects less frames of the movie than IID. • Problems: • MATLAB created 2D frames, instead of 3D. • Cut -off video signals during decoding. • Adding lost pictures and erasing created ones distorted some of the results. • Though the used quality measurements aren’t ideal, they agree with the theory, and represented well the quality a human eye would notice.

19. Summary - PSNR • PSNR isn’t the ideal measurement of the received movie quality. Reasons: • Each frame is analyzed separately, with no consideration of time sequence. A measurement for video quality should consider time sequence. • The PSNR result doesn’t determine the picture quality, because it uses a comparison, instead of an absolute value.

20. Summary - MTF • The distortion of the signals isn’t linear, thus MTF doesn’t represent only the smearing of the edge response. • Legal frame: MTF(f=0)=1. Other values represent other forms of degradation. • Number of legal frames is a very small portion of the total number of frames in the movie.

21. Summary- Power Spectrum • Conclusion is achieved by comparing results of several simulations on a vector, with different parameters.

22. The End