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

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

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

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 B frame P frame B frame P frame B frame P frame

8. MPEG Movies Cirinout.mpg Received.mpg cirinout 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 4. MTF 3. LSF 1. Image 2. Gray Level 1 xx x x f f 1 Ideal edgeSmeared Edge False response

14. Results - Example

15. Results - PSNR Pe=0.02 BurstIID

16. Results - MTF Pe=0.01 Burst IID

17. Results - Power Spectrum BurstIID Pe=0.02

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