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Asymmetrical two-level scalar quantizer with extended Huffman coding for compression of Laplacian source
This paper proposes a novel model of the two-level scalar quantizer with
extended Huffman coding. It is designed for the average bit rate to approach
the source entropy as close as possible provided that the signal to
quantization noise ratio (SQNR) value does not decrease more than 1 dB from the
optimal SQNR value. Assuming the asymmetry of representation levels for the
symmetric Laplacian probability density function, the unequal probabilities of
representation levels are obtained, i.e. the proper basis for further
implementation of lossless compression techniques is provided. In this paper,
we are concerned with extended Huffman coding technique that provides the
shortest length of codewords for blocks of two or more symbols. For the
proposed quantizer with extended Huffman coding the convergence of the average
bit rate to the source entropy is examined in the case of two to five symbol
blocks. It is shown that the higher SQNR is achieved by the proposed
asymmetrical quantizer with extended Huffman coding when compared with the
symmetrical quantizers with extended Huffman coding having equal average bit
rates