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Traffic characterization and modeling of wavelet-based VBR encoded video
Author(s) -
Yao-Chang Kuo,
Bijan Jabbari,
Sohail Zafar
Publication year - 1997
Language(s) - English
Resource type - Reports
DOI - 10.2172/505374
Subject(s) - wavelet , codec , computer science , encoder , wavelet packet decomposition , artificial intelligence , algorithm , wavelet transform , pattern recognition (psychology) , real time computing , computer vision , telecommunications , operating system
Wavelet-based video codecs provide a hierarchical structure for the encoded data, which can cater to a wide variety of applications such as multimedia systems. The characteristics of such an encoder and its output, however, have not been well examined. In this paper, the authors investigate the output characteristics of a wavelet-based video codec and develop a composite model to capture the traffic behavior of its output video data. Wavelet decomposition transforms the input video in a hierarchical structure with a number of subimages at different resolutions and scales. the top-level wavelet in this structure contains most of the signal energy. They first describe the characteristics of traffic generated by each subimage and the effect of dropping various subimages at the encoder on the signal-to-noise ratio at the receiver. They then develop an N-state Markov model to describe the traffic behavior of the top wavelet. The behavior of the remaining wavelets are then obtained through estimation, based on the correlations between these subimages at the same level of resolution and those wavelets located at an immediate higher level. In this paper, a three-state Markov model is developed. The resulting traffic behavior described by various statistical properties, such as moments and correlations, etc., is then utilized to validate their model

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