IMPLEMENTATION OF COMPLEXITY REDUCTION ALGORITHM FOR INTRA MODE SELECTION IN H.264/AVC

1. IMPLEMENTATION OF COMPLEXITY REDUCTION ALGORITHM FOR INTRA MODE SELECTION IN H.264/AVC Santosh Kumar Muniyappa Guided by - Dr. Rao

2. Contents • Need for video compression • Motivation • Video coding standards, video formats and quality • Overview of H.264 • Complexity reduction algorithm for intra mode selection • Experimental results • Conclusions and future work • References

3. Need for Video Compression • Growing market for high bit-rate connections, large storage capacity • Insufficient resource to handle uncompressed video • Better proposition is to send high-resolution compressed video than a low-resolution, uncompressed stream over a high bit-rate transmission channel

4. Motivation [2] Removing redundancy in a video clip Only a small percentage of any particular frame is new information Highly complex process • Reduce the overall complexity suitable for handheld devices

5. Timeline of Video Development [10] Inter-operability between encoders and decoders from different manufacturers Build a video platform which helps to interact with video codecs, audio codecs, transport protocols, security and rights management in well defined and consistent ways

6. Video Format [19] CIF - common intermediate format SIF - simple intermediate format SDTV – standard definition television

7. Quality • Specify, evaluate and compare • Visual quality is inherently subjective • PSNR - most widely used objective quality measurement PSNRdB = 10 log10 ((2n − 1)2 / MSE) where, n = number of bits per pixel • SSIM - represents perceptual image quality based on the structural information

8. OVERVIEW OF H.264 / AVC STANDARD • First published by JVT in 2003 • Achieve substantially higher video compression and a network friendly video representation • Built on the concepts of earlier standards such as MPEG-2 and MPEG-4 Visual • 50% reduction in bit-rate • Error resilience • Supports various interactive (video telephony) and non-interactive applications (broadcast, streaming, storage, video on demand)

9. H.264 Video Codec [3]

10. Slice Types [3] I (intra) slice – contains reference only to itself. P (predictive) slice – uses one or more recently decoded slices as a reference (or prediction) for picture construction. B (bi-predictive) slice – works similar to P slices except that former and future I or P slices may be used as reference pictures SI and SP or “switching” slices may be used for transitions between two different H.264 video streams.

11. H.264 Encoder [27]

12. H.264 Decoder [27]

13. Intra Prediction • I – pictures usually have a large amount of information present in the frame. • The spatial correlation between adjacent macro-blocks in a given frame is exploited. • H.264 offers nine modes for intra prediction of 4x4 luminance blocks. • H.264 offers four modes of intra prediction for 16x16 luminance block. • H.264 supports four modes similar to 16x16 luminance block for prediction of 8x8 chrominance blocks.

14. Intra Prediction Modes for 4x4 Luminance Blocks [27]

15. Intra Prediction Modes for 16x16 Luminance Blocks and 8x8 Chrominance Blocks[27]

16. Inter Prediction [1] • Takes advantage of the temporal redundancies that exist among successive frames. • Temporal prediction in P frames involves predicting from one or more past frames known as reference frames.

17. Inter Prediction Modes [11]

18. Integer Transform and Quantization • Transform: • Prediction error block is expressed in the form of transform co-efficients. • H.264 employs a purely integer spatial transform, which is a rough approximation of the DCT. • Quantization: • Significant portion of data compression takes place. • Fifty-two different quantization step sizes can be chosen. • Step sizes are increased at a compounding rate of approximately 12.5%.

19. De-blocking Filter and Entropy Coding • De-blocking filter: • Removes the blocking artifacts due to the block based encoding pattern • In-loop de-blocking filter • Entropy coding: • Assigning shorter code-words to symbols with higher probabilities of occurrence, and longer code-words to symbols with less frequent occurrences. • CAVLC and CABAC

20. H.264 Profiles [27]

21. Complexity Reduction Algorithm For Intra Mode Selection • Existing intra prediction algorithm in H.264 using RDO examines all possible combinations of coding modes. • Mode combinations for each MB sums up to 592. • This research proposes a complexity reduction algorithm using simple directional masks and neighboring modes. • Reduces the number of mode combinations into 132 at the most, with negligible loss of PSNR and SSIM with a slight bit-rate increase.

22. Rate Distortion Optimization • Lagrangian multiplier λMODE = 0.85x 2(QP-12)/3 • Cost = D + λ MODE x R • N8 – number of modes of an 8x8 chroma block N4 – number of modes of a 4x4 luma block N16 – number of modes of a 16x16 luma block Computing the best mode for one macro block: N8x (16xN4 + N16) = 4 x (16 x 9 + 4) = 592

23. Proposed Intra Mode Selection Algorithm for a 4x4 Luma Block [16] Diff = |a – m| + |b – n| + |c – o| + |d – p|, for vertical direction Diff = |a – d| + |e – h| + |i – l| + |m – p|, for horizontal direction Diff = |c – i| + 2·|d – m| + |h – n|, for diagonal down left direction Diff = |b – l| + 2·|a – p| + |e – o|, for diagonal down right direction Diff = |a – n| + 2·|b – o| + |c – p|, for vertical right direction Diff = |a – h| + 2·|e – l| + |i – p|, for horizontal down direction Diff = |b – m| + 2·|c – n| + |d – o|, for vertical left direction Diff = |e – d| + 2·|i – h| + |m – l|, for horizontal up direction

24. Continued… [16] Step 1 - For a 4x4 luma block, obtain avg and S Step 2a - If S is larger than a threshold, T1, carry out RDO procedure for at most four candidate modes: two modes with minimum and second minimum Diff, and at most two modes from adjacent blocks. In this case, DC mode of adjacent blocks is excluded from RDO procedure. Step 2b - If S is smaller than a threshold, T1, carry out RDO procedure for at most four candidate modes: one mode with minimum Diff, at most two modes from adjacent blocks, and DC mode. Note: T1 is set to 32

25. Proposed Intra Mode Selection Algorithm for a 16x16 Luma Block • Step 1 - Examine sizes of adjacent blocks: if both blocks (upper block and left block) are 16x16, go to Step 2, otherwise go to Step 4. • Step 2 - Examine modes of adjacent blocks: if both modes are same, go to Step 3, otherwise select the best mode for a 16x16 luma block, which results in the minimum SATD (sum of absolute transformed differences) between two adjacent modes of modeA and modeB. • Step 3 - If both adjacent modes are DC mode, go to Step 4, and otherwise select the best mode for a 16x16 luma block, which results in the minimum SATD between the adjacent mode and DC mode. • Step 4 - Let ΔV be a vertical difference between upper boundary pixels of the current block and boundary pixels of the upper block, and ΔH be a horizontal difference between left boundary pixels of the current block and boundary pixels of the left block.

26. Continued… [16]

27. Continued… • Step5 - Obtain candidate modes by using two difference values, ΔV and ΔH: • if |ΔV − ΔH | is smaller than 2xT2, candidate modes are DC mode and plane mode. • if (ΔV − ΔH) is larger than T2, candidate modes are DC mode and horizontal mode. • if (ΔV − ΔH) is smaller than T2, candidate modes are DC and vertical mode. • The threshold T2 is set equal to 8. • Finally, select the best mode among all candidate modes by choosing the mode with minimum SATD.

28. Experimental Results • I-only type. • Various QP of 10, 20, 28, 34, and 40. • QCIF -100 frames CIF - 30 frames • The results were compared with exhaustive search of JM in terms of the change of PSNR, bit-rate, SSIM, compression ratio, and encoding time. • Intel Pentium Dual Core processor of 2GHz and 2GB memory.

29. Test Sequences [39] CIF and QCIF video sequences (a) bridge-close (b) bridge-far (c) coastguard (d) container (e) mobile

30. CR = Complexity reduction algorithm JM = Joint model

32. CR = Complexity reduction algorithm JM = Joint model

33. CR = Complexity reduction algorithm JM = Joint model

34. CR = Complexity reduction algorithm JM = Joint model

35. CR = Complexity reduction algorithm JM = Joint model

36. Conclusions • Comparison of encoding time, PSNR, bit-rate, and SSIM between the JM reference software and complexity reduced encoder at QP, 10, 20, 28, 34 and 40. • Average of 24.93% reduction in encoding time in case of complexity reduced algorithm with negligible loss of PSNR and SSIM and a paltry increase in bit-rate at nearly the same compression ratio. • Hence, this approach of reducing the number of mode combinations in spatial domain using simple directional masks can find its application in low complexity devices like mobile or any handheld device.

37. Future Work • The complexity reduction algorithm was implemented for CIF and QCIF format video sequences. The idea can be extended further to other video formats like 4SIF and HD. • The complexity reduction algorithm was integrated in to JM 18.0 reference software, it can be integrated to other open source H.264 softwares like X264 and performance analysis can be done. • Since the aim is to reduce the overall complexity suitable for handheld devices with limited computing resources, algorithms which reduce the mode combinations in inter-prediction can also be integrated with this complexity reduced intra-prediction algorithm.

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42. Thank You 