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Scalar Quantization-9

Elsevier Inc.
DOI: 10.1016/b978-012620862-7/50009-2
  • Design


Publisher Summary In many lossy compression applications one requires to represent each source output using one of a small number of codewords. The number of possible distinct source output values is generally much larger than the number of codewords available to represent them. The process of representing a large—possibly infinite—set of values with a much smaller set is called “quantization.” This chapter provides a brief overview of quantization. Quantization is a very simple process. However, the design of the quantizer has a significant impact on the amount of compression obtained and loss incurred in a lossy compression scheme. In practice, the quantizer consists of two mappings: an encoder mapping and a decoder mapping. The encoder divides the range of values that the source generates into a number of intervals. Each interval is represented by a distinct codeword. The encoder represents all source outputs that fall into a particular interval by the codeword representing that interval. The decoder generates a reconstruction value. Because a codeword represents an entire interval and there is no way of knowing which value in the interval was actually generated by the source, the decoder puts out a value that, best represents all values in the interval.

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