Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
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We consider the problem of optimal bit allocation in various forms of predictive coding, where the predictor itself has errors resulting from previous quantization. The solution to this problem has potential application to many forms of image and video coding where predictive coding is employed. In predictive coding, the input to the quantizer can be decomposed into the innovation, i.e., the part of the quantizer input that is unpredictable given an unquantized predictor, and the quantizer feedback, i.e. the part of the quantizer input signal due to the quantization of the predictor. The natural question that arises is whether it is better to allocate more bits to the predictor since quantization errors persist longer, or to allocate more bits to coding the total residual. This problem is analyzed for predictive video coding through the use of a simple parametric distortion-rate model for the propagation of quantization errors. This model provides a framework in which the optimal bit allocation problem can be solved in the presence of quantizer feedback.