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Adaptive Rate Control for HEVC Visual Communications and Image Processing (VCIP), 2012 IEEE Junjun Si, Siwei Ma, Xinfeng Zhang, Wen Gao 1.

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Presentation on theme: "Adaptive Rate Control for HEVC Visual Communications and Image Processing (VCIP), 2012 IEEE Junjun Si, Siwei Ma, Xinfeng Zhang, Wen Gao 1."— Presentation transcript:

1 Adaptive Rate Control for HEVC Visual Communications and Image Processing (VCIP), 2012 IEEE Junjun Si, Siwei Ma, Xinfeng Zhang, Wen Gao 1

2 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 2

3 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 3

4 Introduction In this paper, for rate modeling, complexities of previous encoded frames are taken into account to decide appropriate QP. For distortion modeling, distortion is modeled as an exponential function of SATD and QP of current frame. Based on the models, a frame level adaptive rate control algorithm is proposed. In addition, a quality smoothing method is designed based on the distortion model. 4

5 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 5

6 Rate Model q-domain  Function of quantization step size and the complexity of residual signal ρ-domain  ρ is the percentage of zero DCT coefficient, the rate is modeled as a linear function of (1- ρ) Proposed model  SATD is used as complexity estimation of the residual signal. 6

7 SATD residual 7

8 Proposed Rate Model The proposed rate model is shown as : Current Frame ID 0.6 8

9 Proposed Rate Model Actually, R = α*X/QP is developed from the implicit rate model used in the x264 codec. 9

10 Proposed Distortion Model 10

11 Proposed Distortion Model According to the relationship shown previous, the distortion can be modeled as: To verify the accuracy of the proposed distortion model, the relationship of the estimated distortion and the actual distortion of frames are plotted. 11

12 PSNR Based Quality Smoothing Method Original PSNR is defined as : From previous distortion model, PSNR-QP model can be derived as: 12

13 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 13

14 Proposed Algorithm for LD coding 14

15 QP Clipping Detail 15

16 Proposed Algorithm for RA coding 16

17 QP Clipping Detail 1.QP adjustment for I frames 2.QP adjustment based on the difference between bitrate error 3.Clipping again for quality smoothness Bitrate Error 0~1 >1 17

18 Rate Control Algorithm with Quality Smoothing 1.Derive QP using LD/RA rate control algorithm. 2.Guess the PSNR of the current frame. 3.Calculate the average PSNR of the previously encoded frames. 4.Regulate QP by equation below 5.Use the bitrate error to clip QP as a compromise between accuracy and PSNR smoothness 18

19 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 19

20 Experimental Results The proposed rate control scheme has been implemented into HM5.0. 20

21 Experimental Results 21

22 Experimental Results The rate distortion curve of typical test sequences with different resolution and frame rate. 22

23 Experimental Results Results of proposed rate control algorithm with quality smoothing 23

24 Experimental Results Table. 5: Average PSNR and variance of PSNR of typical test sequences with different resolution and frame rate 24

25 Overview Introduction Rate And Distortion Models Adaptive Rate Control Algorithm LD/RA Algorithm Quality Smoothing Algorithm Experimental Results Conclusion 25

26 Conclusion 26


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