Adaptive correlation noise model based Wyner-Ziv distributed video coding

作者：Xiaofei Hu; Xiuchang Zhu^*

来源：International Journal of Digital Content Technology and Its Applications, 2012, 6(14): 456-468.

DOI：10.4156/jdcta.vol6.issue14.54

• Adaptive noise
• Alternating current coefficients
• Coding efficiency
• Coding paradigms
• Correlation noise
• Distributed video coding
• Distribution models
• EM algorithms
• Heavy-tails
• High rate
• Noise models
• Rate distortion performance
• Sudden change
• Video coders
• Wyner-Ziv

Distributed video coding (DVC) is a novel video coding paradigm. One approach to DVC is Wyner-Ziv distributed video coding. The accuracy of the correlation noise model can influence the performance of the video coder directly. In order to enhance the accuracy of the distribution model, EM algorithm based mixture Laplace-uniform distribution model and basic Laplace-uniform distribution model for DCT alternating current coefficients are established. Then the model is selected adaptively using fuzzy inference. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the DISCOVER's noise model. Meanwhile, fuzzy inference based adaptive noise model selection method can reduce the operation complexity to some extent, while not influencing rate-distortion performance.

• 出版日期2012
• 单位南京邮电大学