1. Unequal Loss Protection: Graceful Degradation of Image Quality over Packet Erasure Channels Through Forward Error Correction Alexander E. Mohr, Eva A. Riskin, and Richard E. Ladner IEEE Journal on Selected Areas In Communications, June 2000

2. Outline  Introduction  Background SPIHT  Proposed Framework Formalizing the Framework Algorithm for solving the ULP Problem  Result  Conclusion

3. Introduction  When the number of packets send exceeds transmission capacity, packets are discarded at random.  Each packet can be assigned a unique sequence number It ’ s known which packets are lost  The importance of the packet is different face and background Use the ULP (unequal loss protection) framework to the packets

4. Background-SPIHT  SPIHT Set Partitioning In Hierarchical trees  One progressive image compression algorithm  Progressive transmission Image can be reconstructed quickly from beginning parts of the bit stream Require no traning Low computational complexity

5. SPIHT (cont.)  DCT and Wavelet transform LLHL LHHH

6. SPIHT (cont.) HL LHHH

7. SPIHT (cont.)

8.  Three list are maintained LIP : list of insignificant pixels LIS : list of insignificant set LSP : list of significant pixels  Two Pass Significant map encoding step:  Process the members of LIP  Process the members of LIS Refinement step:  Process the elements of LSP

9. Example of SPIHT  Initialize Threshold = 2 ^ = 16 LIP:  {(0,0), (0,1), (1,0), (1,1)} LIS:  {(0,1)D, (1,0)D, (1,1)D} LSP:  NULL 26613 10 6 4 -77 4 -4 2 -2 4 -3 -2 0

10. Example of SPIHT (cont.)  1st Pass : T = 16  Check LIP: { (0,0), (0,1), (1,0), (1, 1)} (0,0) : 26 > T, send 1 and 0  Move to LSP (0,1) : 6 < T, send 0; (1,0) : |-7| < T, send 0; (1,1) : 7 < T, send 0;  Check LIS: No change {(0,1)D, (1,0)D, (1,1)D} -> 000  Check LSP: {(0,0)} Send the next significant bit 26=(11010) 2 -> send 1 26613 10 6 4 -77 4 -4 2 -2 4 -3 -2 0 signbit

11. Example of SPIHT (cont.)  2nd Pass : T = 8  Check LIP: No change {(0,1), (1,0), (1, 1)} -> 000  Check LIS: {(0,1)D, (1,0)D, (1,1)D} (0,1)D: send 1 13 and 10 : send 10 move to LSP 6 and 4 : send 0 and move to LIP (1,0)D, (1,1)D : send 0 and no change  Check LSP: {(0,0), (0,2), (0,3)} 26=(11010) 2 -> send 1 13=(1101) 2 -> send 1 10=(1010) 2 -> send 1 26613 10 6 4 -77 4 -4 2 -2 4 -3 -2 0

12. SPIHT (cont.)  Property: Each Pass are transmitting one bitplane High compression ratios, but compressed with SPIHT are vulnerable to data loss SPIHT produces an embedded bitstream  The later bits in the bitstream refine earlier bits  The earlier bits are needed for the later bits to be useful

13. Background- FEC  Using Reed-Solomon Codes  Leicher applied a simple three-class system to protect video stream compressed with MPEG I frame : 60% data (M 1 ) P frame : 80% data (M 2 ) B frame : 95% data (M 3 )

14. Proposed Scheme  To assign unequal amounts of FEC to progressive data  The message is divided into L streams such that each stream has one byte of each of N packets

15. Formalizing the Framework  Send a message M  m i the number of data bytes assigned to stream i  f i = N-m i the number of FEC bytes assigned to stream I  L-dimensional FEC vector  includes the byte of M from position to position

16. Formalizing the Framework (cont.)  Define the incremental PSNR of stream I where  Expected PSNR of the received message

17. Formalizing the Framework (cont.)  is the probability that receiver can decode stream i  We want to find a good FEC assignment vector  Using a local search hill-climbing algorithm

18. Algorithm best[*]=(N, N, ….,N); Until best[*] = last[*] do For each stream s = 1 to L For Range from – Q to Q temp[*] = last[*] temp[s]+=Range; if temp[s] N continue; if Q>0 then for all i>s temp[i] = max(temp[s], temp[i]); else for all i< s temp[i] = min(temp[s], temp[i]); Calculate expected PSNR for temp[*] if PSNR(temp[*]) >PSNR(best[*]) then best[*] = temp[*]; For f j-1 < f j

19. Algorithm (cont.)  The search range Q Large Q:  the algorithm will find global optimal  Require more time to run  For every byte of FEC data added to a stream, one byte of data needs to be removed.  The size of each code would need to be send to the decoder as side information

20. Result

21. Result (cont.)

22. Conclusion  Presented the Unequal Loss Protection framework and developed a simple algorithm that assigns FEC to provide graceful degradation  As better progressive compression algorithms than SPIHT are discovered, they can be easily incorporated int the ULP framework