A Framework for Adaptive Scalable Video Coding Using Wyner-Ziv Techniques
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A Framework for Adaptive Scalable Video Coding Using Wyner-Ziv Techniques Huisheng Wang, Ngai-Man Cheung, and Antonio Ortega Integrated Media Systems Center and Department of Electrical Engineering, USC Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089-2564, USA Received 27 March 2005; Revised 31 August 2005; Accepted 12 September 2005 This paper proposes a practical video coding framework based on distributed source coding principles, with the goal to achieve efficient and low-complexity scalable coding. Starting from a standard predictive coder as base layer (such as MPEG-4 baseline video coder in our implementation), the proposed Wyner-Ziv scalable (WZS) coder can achieve higher coding efficiency, by selectively exploiting the high quality reconstruction of the previous frame in the enhancement layer coding of the current frame. This creates a multi-layer Wyner-Ziv prediction “link,” connecting the same bitplane level between successive frames, thus providing improved temporal prediction as compared to MPEG-4 FGS, while keeping complexity reasonable at the encoder. Since the temporal correlation varies in time and space, a block-based adaptive mode selection algorithm is designed for each bitplane, so that it is possible to switch between different coding modes. Experimental results show improvements in coding efficiency of 3–4.5 dB over MPEG-4 FGS for video sequences with high temporal correlation. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
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INTRODUCTION
Scalable coding is well suited for video streaming and broadcast applications as it facilitates adapting to variations in network behavior, channel error characteristics, and computation power availability at the receiving terminal. Predictive coding, in which motion-compensated predictors are generated based on previously reconstructed frames, is an important technique to remove temporal redundancy among successive frames. It is well known that predictive techniques increase the difficulty of achieving efficient scalable coding because scalability leads to multiple possible reconstructions of each frame [1]. In this situation, either (i) the same predictor is used for all layers, which leads to either drift or coding inefficiency, or (ii) a different predictor is obtained for each reconstructed version and used for the corresponding layer of the current frame, which leads to added complexity. MPEG-2 SNR scalability with a single motion-compensated prediction loop and MPEG-4 FGS exemplify the first approach. MPEG-2 SNR scalability uses the enhancement-layer (EL) information in the prediction loop for both base and enhancement layers, which leads to drift if the EL is not received. MPEG-4 FGS provides flexibility in bandwidth adaptation and error recovery because the enhancement layers are coded in “intra-” mode, which results in low coding efficiency especially for sequences that exhibit high temporal correlation.
Rose and Regunathan [1] proposed a multiple motioncompensated prediction loop approach for gen
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