Optimizing Baseline Profile in H

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Presentation transcript:

Optimizing Baseline Profile in H Optimizing Baseline Profile in H.264/AVC Video Coding by Parallel Programming and Fast Intra and Inter prediction BY Under the Guidance of VINOOTHNA GAJULA Dr. K. R. RAO ID 1000803103 MS Electrical Engineer

OBJECTIVE In this project the computational complexity and encoding time of Baseline profile of H.264 are reduced by Using Applying Parallel programming using OPEN MD [1] , [7]. Fast adaptive termination (FAT) algorithm in Intra prediction [2],[8] FAT inter prediction mode decision and motion estimation Optimized Baseline Profile

STEP 1: Executing Parallel programming Applying Parallel programming using OPEN MD [1] , [7]. Fast adaptive termination (FAT) algorithm in Intra prediction [2],[8] FAT inter prediction mode decision and motion estimation Optimized Baseline Profile

Parallel programming simulation results at QP=20 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 97.005 (62.276) 42.15600 3.90000 0.98700 920.96000 Bridge_far_qcif.yuv 131.717 (98.034) 42.22400 30.00000 0.96650 428.95000 coastguard_qcif.yuv 181.301 (144.380) 42.05400 4.05000 0.98730 919.14000 Bridge_close_cif.yuv 44.882 (37.539) 43.16300 3.56000 0.98890 160.26200 Bridge_far_cif.yuv 43.367 (36.046) 42.28400 9931.00000 814.19000 coastguard_cif.yuv 42.688 (35.946) 43.00100 3.54560 0.98570 1426.42000

Parallel programming simulation results at QP=30 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 90.908 (68.661) 33.535 28.821 0.9234 60.92 Bridge_far_qcif.yuv 107.623 (82.324) 37.281 12.33 0.9309 6.53 coastguard_qcif.yuv 172.775 (147.191) 32.886 33.571 0.8988 182.96 Bridge_close_cif.yuv 40.342 (35.506) 35.386 33.444 0.9349 333.41 Bridge_far_cif.yuv 38.724 (34.526) 36.664 15.45 130.1 coastguard_cif.yuv 43.674 (38.057) 35.51 26.93671 492.3

Parallel programming simulation results at QP=40 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 94.156 (73.569) 27.89980 105.53100 0.77910 6.24000 Bridge_far_qcif.yuv 83.737 (64.839) 32.31800 38.13040 0.88700 3.78000 coastguard_qcif.yuv 130.818 (111.265) 26.60200 143.93300 0.65220 24.72000 Bridge_close_cif.yuv 39.849 (35.566) 29.92700 95.49000 0.80660 115.38000 Bridge_far_cif.yuv 38.796 (34.820) 32.29800 52.09100 0.72240 57.23000

STEP 2: FAT Algorithm in Intra prediction. Applying Parallel programming using OPEN MD [1] , [7]. Fast adaptive termination (FAT) algorithm in Intra prediction [2],[8] FAT inter prediction mode decision and motion estimation Optimized Baseline Profile

FAT algorithm in Intra prediction simulation results at QP=20 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 129.582 (86.578) 42.164 3.58 0.987 921.89 Bridge_far_qcif.yuv 143.143 (106.564) 42.27 3.859 0.967 442.07 coastguard_qcif.yuv 228.794 (183.037) 42.071 4.042 0.9878 922.14 FAT algorithm in Intra prediction simulation results at QP=30 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 130.102 (98.549) 33.56300 28.53550 0.92350 59.68000 Bridge_far_qcif.yuv 123.152 (94.672) 37.21400 12.35000 0.93130 6.11000 coastguard_qcif.yuv 235.493 (200.734) 32.88300 33.58000 0.90310 184.09000

Total Encoding Time (ME Time) Parallel programming simulation results at QP=40 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 125.279 (98.194) 27.79700 107.99474 0.77230 5.93000 Bridge_far_qcif.yuv 116.707 (90.830) 31.97500 41.26590 0.88320 3.80000 coastguard_qcif.yuv 187.518 (159.681) 26.45800 148.64410 0.66440 25.36000

STEP 3: Merging the parallel programming and FAT Algorithm in Intra prediction. Applying Parallel programming using OPEN MD [1] , [7]. Fast adaptive termination (FAT) algorithm in Intra prediction [2],[8] FAT inter prediction mode decision and motion estimation Optimized Baseline Profile

Merged simulation results at QP=20 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 114.850 (76.966) 42.14400 3.97800 0.98690 922.32000 Bridge_far_qcif.yuv 127.483 (95.016) 42.25100 3.80000 0.96690 439.11000 coastguard_qcif.yuv 204.227 (163.69) 42.05300 4.06000 0.98740 919.11000 Merged simulation results at QP=30 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 115.527 (87.745) 33.55400 28.69250 0.92340 60.60000 Bridge_far_qcif.yuv 110.229 (85.282) 37.21000 12.36228 0.9313 60.66 coastguard_qcif.yuv 209.184 (178.861) 32.87500 33.45740 0.98400 182.17000

Total Encoding Time (ME Time) Merged simulation results at QP=40 Sample Video Inputs Total Encoding Time (ME Time) PSNR MSE SSIM Bit Rate Bridge_close_qcif.yuv 111.810 (87.979) 27.79400 108.08000 0.77230 6.28000 Bridge_far_qcif.yuv 104.146 (81.516) 31.97500 41.26700 0.88320 4.01000

Pending Steps Simulation of FAT Inter prediction and merging the parallel programming and FAT Algorithm in Intra prediction and FAT algorithm in inter and ME prediction. Applying Parallel programming using OPEN MD [1] , [7]. Fast adaptive termination (FAT) algorithm in Intra prediction [2],[8] FAT inter prediction mode decision and motion estimation Optimized Baseline Profile