1. Flexible Fast Block Matching Algorithm Design based on Complexity-Distortion Optimization Pol Lin Tai, Chii Tung Liu, Shih Yu Huang*, Jia Shung Wang Department of Computer Science National Tsing Hua University, Taiwan, R.O.C. *Department of Information Management Ming Chuan University, Taiwan, R.O.C.

2. Outline Introduction - Block Motion Estimation Traditional Fast Block Motion Estimation Adaptive Complexity-Distortion Block Motion Estimation Experimental Results Conclusions

3. Full-Search Block Matching Search area Current block motion vector = ),( minarg ),( vuMAE vu vectorMAE (-3,-3)50 (-2,-3)70 (-1,-3)45  (-2,2)0  (3,3)120   Frame n-1Frame n x y 0 12 3 -2 -3 1 2 3 -2 -3 Motion vector

4. Three-Step Search Fast Block Matching Algorithm 4 2 xxx xx xxx 1 motion vector = Pvu,P- and ),,(minarg ),(  vuMAE vu Current frame 16 Referenced frame Search area Motion vector Current block  fast block matching - three-step search, four-step search - new three-step search  reduce check point (u,v)

5. Problems of the Traditional BM (1) Fixed Computational Complexity 10log(check point) 400 500 600 700 800 900 1000 1100 4914192429 FSBM TSS New-TSS FSS MSE

6. Problems of the Traditional BM (cont.) (2) Complexity-Distortion Optimization 25  4=100 :1+9+1+25 = 36 Block 1Block 2block3Block 4 The search path for TSS 50 60 40 30 80 70 60 50 Initial mv (0,0) Step one (8 check points) Step two (8 check points) Step three (8 check points)

7. Complexity-Distortion Optimization BM 10log(check point) 400 500 600 700 800 900 1000 1100 4914192429 CDOBM FSBM TSS New-TSS FSS MSE  flexible computational complexity  better complexity-distortion performance

8. Complexity-Distortion Optimization 50 60 40 30 80 70 60 50  In Rate-Distortion Optimization  trellis system - dynamic programming Viterbi algorithm In Complexity-Distortion Optimization  MSE Benefit ?  Non-Reusable  Heuristic search algorithm 0 20

9. How to Define MSE benefit  In each checking step, select the block that could achieve the maximum improved distortion benefit to apply searching procedure Block 1Block 2block3Block 4 50 60 40 34 30 20 80 65 60 50 Initial mv (0,0) Step one (8 check points) Step two (8 check points) Step three (8 check points) 1234

10. Predictive Complexity-Distortion Benefit List 300 Block 1 500 Block 2 200 Block 3 400 Block 4 100 Block 5 MSE: 300 Block 1 500 Block 2 200 Block 3 400 Block 4 100 Block 5 benefit: Assign benefit Sort 500 Block 2 400 Block 4 300 Block 1 200 Block 3 100 Block 5 Predictive Complexity-Distortion Benefit List

11. Updating PCDB List Select Block 2 to check candidate blocks (MSE check =250) 500 Block 2 400 Block 4 300 Block 1 200 Block 3 100 Block 5 PCDB List Update PCDB List 400 Block 4 350 Block 2 300 Block 1 200 Block 3 100 Block 5 Benefit 2 = 0.7  Benefit 2 MSE check <MSE 2 MSE check >MSE 2 Update PCDB List 400 Block 4 Block 1 250 Block 2 200 Block 3 100 Block 5 Benefit 2 =MSE check 300

12. Flexible Fast Block Matching Algorithm Design Select the first block from PDCB list Checking candidate blocks Yes No End Initialize PCDB list Start Updating PCDB list Total complexity > target complexity ?

13. Checking Candidate Motion Vector Select Block 2 to check candidate motion vector 500 Block 2 400 Block 4 300 Block 1 200 Block 3 100 Block 5 PCDB List Search pattern FSBM3-Step

14. Experimental Results QCIF: “ Miss America ”, “ Suzie ” SIF: “ Football ” full-search block matching, 3-step search, new 3-step search, 4-step search frame rate: 15Hz and 7.5Hz search area: SIF (-15,15), QCIF (-7,7)  is set as 0.8

15. Experimental Results (cont.) The complexity-distortion performance comparison for the QCIF "Miss America" with (a) frame rate 15Hz 7 9 11 13 15 17 19 01020304050 flexible-FSBM flexible-TSS flexible-New-TSS flexible-FSS FSBM TSS New-TSS FSS Complexity (10  ln(check point)) Distortion (MSE)

16. Experimental Results (cont.) The complexity-distortion performance comparison for the QCIF "Miss America" with (a) frame rate 7.5Hz 11 16 21 26 31 36 41 01020304050 flexible-FSBM flexible-TSS flexible-New-TSS flexible-FSS FSBM TSS New-TSS FSS Complexity (10  ln(check point)) Distortion (MSE)

17. Experimental Results (cont.) video frame rate LowHighLowHigh 15FSBMNew-TSSTSSFSS 7.5FSSNew-TSSTSSFSS 15FSBMNew-TSSTSSFSS 7.5FSSNew-TSSTSSFSS 15FSSNew-TSSFSBMFSS 7.5TSSNew-TSSFSBMFSS Football The Best Algorithm The Worst Algorithm Miss America Suzie complexity The performance summary of the flexible BMAs

18. Conclusions Discuss how to utilize the limited computational complexity of the block matching algorithm to achieve the maximum quality of the compensated image under a target computational complexity Propose predictive complexity-distortion benefit list technique The flexible block matching algorithm design not only improves the efficiency of the traditional BMAs, but also provides a flexible motion estimation tool that allows user to terminate it at any computational complexity