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Wyner-Ziv video coders perform simple intra-frame encoding and complex inter-frame decoding. This feature makes this type of coder suitable for applications that require low-complexity encoders. Video coding algorithms provide coding modes and parameters so that encoders can fulfill rate constraints and improve the coding efficiency. However, in most Wyner-Ziv video coders, no algorithm is used to optimally choose the coding modes and parameters. In this paper, we present a rate control algorithm for pixel-domain Wyner-Ziv video coders. Our algorithm predicts the rate and distortion of each video frame as a function of the coding mode and the quantization parameter. In this way, our algorithm can properly select the best mode and quantization for each video frame. We show experimentally that, even though the rate and distortion cannot be accurately predicted in Wyner-Ziv video encoders, rate constraints are approximately fulfilled and good coding efficiency is obtained by using our algorithm.

Generally speaking, rate scalable video systems today are evaluated operationally, meaning that the algorithm is implemented and the rate-distortion performance is evaluated for an example set of inputs. However, in these cases it is difficult to separate the artifacts caused by the compression algorithm and data set with general trends associated with scalability. In this paper, we derive and evaluate theoretical rate-distortion performance bounds for both layered and continuously rate scalable video compression algorithms which use a single motion-compensated prediction (MCP) loop. These bounds are derived using rate-distortion theory based on an optimum mean-square error (MSE) quantizer, and are thus applicable to all methods of intraframe encoding which use MSE as a distortion measure. By specifying translatory motion and using an approximation of the predicted error frame power spectral density, it is possible to derive parametric versions of the rate-distortion functions which are based solely on the input power spectral density and the accuracy of the motion-compensated prediction. The theory is applicable to systems which allow prediction drift, such as the data-partitioning and SNR-scalability schemes in MPEG-2, as well as those with zero prediction drift such as fine granularity scalability MPEG-4. For systems which allow prediction drift we show that optimum motion compensation is a sufficient condition for stability of the decoding system.

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