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EFFICIENT PARALLEL FRAMEWORK FOR H.264 AVC DEBLOCKING FILTER ON MANY-CORE PLATFORM Yongdong Zhang, Member, IEEE, Chenggang Yan, Feng Dai, and Yike Ma.

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Presentation on theme: "EFFICIENT PARALLEL FRAMEWORK FOR H.264 AVC DEBLOCKING FILTER ON MANY-CORE PLATFORM Yongdong Zhang, Member, IEEE, Chenggang Yan, Feng Dai, and Yike Ma."— Presentation transcript:

1 EFFICIENT PARALLEL FRAMEWORK FOR H.264 AVC DEBLOCKING FILTER ON MANY-CORE PLATFORM Yongdong Zhang, Member, IEEE, Chenggang Yan, Feng Dai, and Yike Ma

2 Outline  Introduction  Method  A. Boundary Strength Computation (BSC)  B. Edge Discrimination and Filtering (EDF)  Experimental Results  Q & A

3 Introduction #1  Deblocking Filter  boundary strength computation (BSC) imbalance  edge discrimination and filtering (EDF) data dependency

4 Introduction #2  Imbalance stall core1 core2 core3 core4

5 Introduction #3  Data dependency frame1

6 Method #1  For every edge, because of complex “if” instructions, they split the deblocking filter into three parts: BSC, ED, and filtering. [39] GSAIM, Chung-Ang University, Seoul, “Variable block-based deblocking filter for H.264/AVC on low-end and low-bit rates terminals,” Signal Process.: Image ommun., vol. 25, no. 4, pp. 255–267, 2010.

7 Method #2  BSC is determined according to the coding information, such as coding mode and coded residues, which is not influenced by the output of other parts.  The BS value determines the strength of filtering.

8 Method #3  They find that most of the deblocking computation resources are spent on BSC, which is independent from the EDF.  parallelize BSC first and apply 2D-wavefront method to the EDF.

9 Method #4  Two problems  BSC Imbalance  EDF Dependency

10 Method.A  boundary strength computation (BSC)

11 Method.A #1  They find that the BSC has biased statistical distribution in the temporal domain, which can be modeled as a Markov chain. And they characterize the Markov chain as an empirical transition probability matrix (ETPM).  Huffman tree

12 Method.A #2  The current edge BS value has something to do with the corresponding edge BS value in a prior same- type frame.

13 Method.A #3

14 Method.A #4

15 Method.A #5

16 Method.B  edge discrimination and filtering (EDF)

17 Method.B #1  Luma Component

18 Method.B #2

19 Method.B #3  Strong Vertical Boundary(SVB) and Strong Horizontal Boundary(SHB)

20 Method.B #4

21 Method.B #5  Several PSAs make up one independent pixel connected area (IPCA).

22 Method.B #6  Chrome Component [46]

23 Method.B #7

24 Method

25 Experimental Results #1

26 Experimental Results #2

27 Experimental Results #3

28 Experimental Results #4

29 Experimental Results #5

30 Experimental Results #6

31 Experimental Results #7

32 Experimental Results #8

33 Experimental Results #9

34 Experimental Results #10

35 Q & A


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