分布式编码中广义伽马分布相关噪声模型研究

doi:10.11959/j.issn.1000-436x.2016050

Abstract

Abstract:

Due to the inaccuracy of modeling the correlated noise (CN) with Laplacian distribution,the rate-distortion performance of DVC is relatively low.CN modeling via generalized Gamma (GGA)distribution was proposed for pix-el-domain DVC.Statistical features of the CN modeling were analyzed.It was found that Laplacian distribution peak was lower than actual CN distribution.GGA distribution was exploited to fit CN and the GGA distribution parameters were estimated online.The simulation results indicate that the proposed model can more accurately reflect the statistics fea-tures of CN,improve rate distortion performance,and reduce computation complexity.

Key words: distributed video coding, correlation noise model, generalized Gamma distribution, Laplacian distribution

Jie-ping LIU,Qin-ling WANG,Yue-sheng HE,Gang WEI. Research on correlation noise modeling of a generalized Gamma distribution in distributed coding[J]. Journal on Communications, 2016, 37(3): 33-39.

Figures/Tables 6

References 20

[1]	SLEPIAN J D , WOLF J K . Noiseless coding of correlated information sources[J]. IEEE Transactions on Information Theory, 1973,19(4): 471-480.
[2]	WYNER A , ZIV J . The rate-distortion function for source coding with side information at the decoder[J]. IEEE Transactions n Information Theory, 1976,22(1): 1-10.
[3]	AARON A , ZHANG R , GIROD B . Wyner-Ziv coding of motion video[C]// Asilomar Conference on Signals,Systems and uters.Pacific Grove, CA,USA,IEEE, c2002:240-244.
[4]	WANG A H , ZHAO Y , BAI H H . Robust multiple description distri-buted video coding using optimized zero-padding[J]. Science in China Series F:Information Sciences, 2009,52(2): 206-214.
[5]	ABOU-ELAILAH A , DUFAUX F , FARAH J , et al. Fusion of global and local motion estimation using foreground objects for distributed video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2014,25(6): 973-987.
[6]	SONG X D , PENG X L , XU J Z , et al. Cloud-based distributed image coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2015,25(12): 1.
[7]	BRITES C , PEREIRA F . Correlation noise modeling for efficient pixel and transform domain Wyner-Ziv video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2008,18(9): 1177-1190.
[8]	DELIGIANNIS N , MUNTEANU A , CLERCKX T , et al. Correlation channel estimation in pixel-domain distributed video coding[C]// Image Analysis for Multimedia Interactive Serv London, UK, c2009:93-96.
[9]	DELIGIANNIS N , MUNTEANU A , WANG S , et al. Maximum like-lihood Laplacian correlation channel estimation in layered Wyner-Ziv coding[J]. IEEE Transactions on Signal Processing, 2014,62(4): 892-904.
[10]	王凤琴，樊养余，赵炯，等. 基于变换域 Wyner-Ziv 视频编码的相关噪声模型[J]. 数据采集与处理， 2009,24(5): 609-614. WANG F Q , FAN Y Y , ZHAO J , et al. Correlation noise model for transform domain Wyner-Ziv video coding[J]. Journal of Data Acqui-sition ＆ Processing, 2009,24(5): 609-614.
[11]	房胜，李哲，梁永全，等. 分布式视频编码虚拟依赖信道模型研究[J]. 计算机学报， 2009,32(7): 1404-1412. FANG S , LI Z , LIANG Y Q , et al. Research of the virtual dependency channel in distributed video coding[J]. Chinese Journal of Computers, 2009,32(7): 1404-1412.
[12]	WANG S , CUI L J , STANKOVI C L , et al. Adaptive correlation estimation with particle filtering for distributed video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012,22(5): 649-658.
[13]	FANG Y . Asymmetric Slepian-Wolf coding of nonstationarily- corre-lated M-ary sources with sliding-window belief propagation[J]. IEEE Transactions on Communications, 2013,61(12): 5114-5124.
[14]	杨春玲，吴娟 . 分布式视频编码中基于改进 FCM 聚类的相关噪声模型估计[J]. 中国图象图形学报， 2014,19(2): 0185-0193. YANG C L , WU J . Correlation noise modeling based on improved fuzzy C-means clustering in distributed video coding[J]. Journal of Image and Graphics, 2014,19(2): 0185-0193.
[15]	WESTERLAKEN R P , GUNNEWIEK R K , LAGENDIJK R L . The role of the virtual channel in distributed source coding of video[C]// IEEE International Conference on Image Processi g. Genoa,Italy, c2005:581-584.
[16]	MAUGEY T , GAUTHIER J , PESQUET-POPESCU B , et al. Using an exponential power model for Wyner-Ziv video coding[C]// IEEE Inter-national Conference on Acoustics,Speech and Signal Processing, Dallax Texas, c2010:2338-2341.
[17]	尹明，蔡述庭，谢云 . 基于高斯混合模型的Wyner-Ziv视频编码[J]. 计算机学报， 2012,35(1): 173-182. YIN M , CAI S T , XIE Y . Wyner-Ziv video coding based on Gaussian mixture mode[J]. Chinese Journal of Computers, 2012,35(1): 173-182.
[18]	WINGO D R . Computing maximum-likelihood parameter estimates of the generalized Gamma distribution by numerical root isolation[J]. IEEE Transactions on Reliability, 1987,R-36(5): 586-590.
[19]	JONES B , WALLER W G , FELDMAN A . Root isolation using func-tion values[J]. BIT Numerical Mathematics, 1978,18(3): 311-319.
[20]	ASCENSO J , BRITES C , PEREIRA F . Improving frame interpolation with spatial motion smoothing for pixel domain distributed video cod-ing[C]// 5th EURASIP Conference on Speech and Image Processing,Multimedia Communications and Services, Slo Repub-lic: EURASIP, c2005:593-598.

Metrics

Recommended 0

No Suggested Reading articles found!

显著性水平	GGA	GGD	Lap
0.01	100%	86.67%	65.00%
0.05	100%	86.67%	56.67%
0.10	100%	86.67%	51.67%
0.25	100%	83.33%	38.33%

视频序列	M	GGA GGD与对比		GGA Laplacian与对比
视频序列	M	码率降低/(Kbit·s^{- 1})	降低百分比/%	码率降低/(Kbit·s^{- 1})	降低百分比/%
Mother	1	6.68	21.56	17.28	41.55
	2	14.87	19.83	29.50	32.91
	3	26.73	19.22	45.16	28.68
	4	41.47	17.22	62.67	23.91
Soccer	1	27.30	38.28	87.32	66.49
	2	64.16	34.59	128.56	51.45
	3	109.90	28.17	197.56	41.35
	4	160.59	24.58	292.26	37.23

视频序列	与GGD模型对比	与Laplacian模型对比
Foreman	-22.24%	-38.02%
Hall	-26.85%	-53.57%
Soccer	-22.77%	-44.55%
Mother	-26.57%	-39.71%

Research on correlation noise modeling of a generalized Gamma distribution in distributed coding

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 20

Related Articles 6

Metrics

Recommended 0

[1]	HENJian C,Chao HUI,Yong-hong KUO. Rate control algorithm for no-feedback distributed video coding [J]. Journal on Communications, 2014, 35(6): 32-38.
[2]	. Rate control algorithm for no-feedback distributed video coding [J]. Journal on Communications, 2014, 35(6): 5-38.
[3]	Ming YIN,Shu-ting CAI,Yun XIE,Yun ZHANG. Virtual channel model for distributed video coding accounting for quantization noise [J]. Journal on Communications, 2012, 33(2): 141-148.
[4]	Hao QIN,Xue-lu PENG,Bin SONG,Hai-hua LIU. Robust reconstruction of Wyner-Ziv frame for no-feedback distributed video coding [J]. Journal on Communications, 2012, 33(1): 167-173.
[5]	Bin SONG,Ming-ming YANG,Hao QIN,Hong HE. No-feedback rate control algorithm for Wyner-Ziv video coding [J]. Journal on Communications, 2011, 32(12): 1-7.
[6]	Bin SONG,Hong HE,Hai-hua LIU,Hao QIN. Research on side information generation algorithm for Wyner-Ziv video coding [J]. Journal on Communications, 2010, 31(12): 97-103.