Vector quantization and signal compression
Vector quantization and signal compression
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The vector quantization scheme has proven to be very effective in speech and image coding. One of the most important steps in the whole process is the design of the codebook. The codebook is generally designed using the LBG algorithm, that is in essence a clustering algorithm which uses a large training set of empirical data that is statistically representative of the image to be quantized. In order to avoid some inherent problems related to the generation of the codebook using the LBG algorithm, a stochastic generation of the codebook has already been proposed as an efficient alternative. In this case, the codebook is generated according to some previously defined model of the image to be encoded and not according to some specific data sequence. The objective of this paper is to report on new results using some improved models for the generation of the codebook and further refinements on the visual aspect of the encoded image. Good visual results are shown in the range of 0.5 - 0.8 bits/pixel. For completeness purposes, a summary of the original stochastic vector quantizer scheme is also provided.